Produced By: In Association With: Hosted By: Benefits of Attending: irmuk.co.uk/edbi2016 Case Studies & Contributors Include: • IFC World Bank • The British Army • Barclays • Merck Sharp & Dohme • Visa Europe • Royal Mail • Ford • Nordea Bank • Environment Agency • Zurich UK General Insurance • City of Amsterdam • IBM • GE Capital • Raiffeisenbank • Volkswagen Pon Financial Services • Generali • Boehringer Ingelheim Pharma • Yorkshire Building Society Group • STANLIB • Dublin City University • Friesland Campina • Computer Weekly • Defence Infrastructure Organisation • Cloudera • Talenom • Trifacta • Sberbank CZ • IDG • Zipcar Int • Sonovate • OulalaGames Group Booking Discounts Available Lt Col Mike Servaes Data Strategy British Army Sue Geuens Head: Data Standards & Best Practice Barclays & DAMA Int Rhys David Head of Business Intelligence & IT Delivery Gocompare.com Roberto Maranca Managing Director Enterprise Data GE Capital Pablo Casullo BI Development & Strategy Lead Merck Sharp & Dohme Rick van der Lans R20/Consultancy Len Silverston Universal Data Models William McKnight Consultant McKnight Consulting Group Graeme Simsion International Best- Selling Novelist (and Former Data Modeller) Mike Ferguson Intelligent Business Strategies • Rick van der Lans • Sue Geuens • Mike Ferguson • Jan Henderyckx • Malcolm Chisholm • William McKnight • Chris Bradley • Len Silverston • Graeme Simsion • Mike Simons • Daragh O Brien • Nigel Turner • Jos van Dongen • Brian McKenna • Garry Manser • Gwen Thomas • Peter Thomas • Neil Storkey • Glen Bell • Anthony Algmin Speakers Include: • Learn From Your Peers. The conference provides an interactive forum where Data and BI Professionals can meet, discuss and debate how best to rise to the challenges faced by their organisations today and in the future. The 2015 conference attracted delegates from 30 countries. • Five Conference Tracks with More Than 60 Sessions with a Focus on Case Studies. Learn from other organisations past successes and challenges from over 30 case studies. The five tracks include a one day Big Data track and a one day Data Innovation track.. • Sixteen Half Day Workshops. Choose from an unparalleled range of workshops on specific topics to get you quickly up-to-speed or fine tune your performance on Data and BI Essentials. Choose from introductory or advanced levels. • Full Day Workshops. Choose from four full day conference workshops. Enhance your in-depth knowledge and skills on Enterprise Data Management and BI best practices. • Wide Variety of Topics Providing an Excellent Mix of Theory, Visions and Practical Implementations. Topics include Agile BI, Big Data Modelling, Data/ Information Maturity Assessment, Data Quality, Logical Data Warehouse, Big Data Platform Fundamentals, SQL and NoSQL, Data Protection Regulation, Information Governance, Data Funding, Predictive Analytics, Self Service & Collaborative BI, Getting Business Value from the IoT, Big Data Technology and Use Cases, Data Virtualisation, Information Architecture, Enterprise Data Integration, Data Governance, MDM and many more.... • Data and BI Solution Providers. Discuss your Data & BI challenges with relevant solution providers. • Attendee Satisfaction. Of those that replied 99% of the 2015 attendees said that they would recommend attending this conference to a colleague. Sponsors, Supported By & Media Sponsors: Technology Evaluation Centers CDO Forum 9 November Attendance by invitation only 7-10 November 2016 Radisson Blu Portman Hotel London
Transcript
Produced By: In Association With: Hosted By:
Benefits of Attending:
irmuk.co.uk/edbi2016
Case Studies & Contributors Include:
• IFC World Bank• The British Army• Barclays• Merck Sharp
& Dohme• Visa Europe• Royal Mail• Ford• Nordea Bank• Environment Agency• Zurich UK General
Insurance• City of Amsterdam• IBM• GE Capital• Raiffeisenbank• Volkswagen Pon
• Rick van der Lans• Sue Geuens• Mike Ferguson• Jan Henderyckx• Malcolm Chisholm• William McKnight• Chris Bradley• Len Silverston• Graeme Simsion• Mike Simons
• Daragh O Brien• Nigel Turner• Jos van Dongen• Brian McKenna• Garry Manser• Gwen Thomas• Peter Thomas• Neil Storkey• Glen Bell• Anthony Algmin
Speakers Include:
• Learn From Your Peers. The conference provides an interactive forum where Data and BI Professionals can meet, discuss and debate how best to rise to the challenges faced by their organisations today and in the future. The 2015 conference attracted delegates from 30 countries.
• Five Conference Tracks with More Than 60 Sessions with a Focus on Case Studies. Learn from other organisations past successes and challenges from over 30 case studies. The five tracks include a one day Big Data track and a one day Data Innovation track..
• Sixteen Half Day Workshops. Choose from an unparalleled range of workshops on specific topics to get you quickly up-to-speed or fine tune your performance on Data and BI Essentials. Choose from introductory or advanced levels.
• Full Day Workshops. Choose from four full day conference workshops. Enhance your in-depth knowledge and skills on Enterprise Data Management and BI best practices.
• Wide Variety of Topics Providing an Excellent Mix of Theory, Visions and Practical Implementations. Topics include Agile BI, Big Data Modelling, Data/Information Maturity Assessment, Data Quality, Logical Data Warehouse, Big Data Platform Fundamentals, SQL and NoSQL, Data Protection Regulation, Information Governance, Data Funding, Predictive Analytics, Self Service & Collaborative BI, Getting Business Value from the IoT, Big Data Technology and Use Cases, Data Virtualisation, Information Architecture, Enterprise Data Integration, Data Governance, MDM and many more....
• Data and BI Solution Providers. Discuss your Data & BI challenges with relevant solution providers.
• Attendee Satisfaction. Of those that replied 99% of the 2015 attendees said that they would recommend attending this conference to a colleague.
Sponsors, Supported By & Media Sponsors:
Technology Evaluation Centers
CDO Forum9 November
Attendance by invitation only
7-10 November
2016
Radisson Blu Portman Hotel
London
Leading Digital Strategy – Enterprise Data as an Asset Sakari Jorma, Chief Digital Officer & CTO, Talenom
Digital commerce has shown tremendous growth figures in recent years, while global penetration is still below 5% of total sales. Mobile commerce, business intelligence and smart infrastructure are key in driving companies and consumers and ways of doing business. However, simply implementing or using digital technologies is not enough. In general, effective digital strategies are less about acquiring and implementing the right technology than about reconfiguring your business to take advantage of the information these technologies enable. Companies must bring together varieties of digital technologies integrated across people, process and functions in order to achieve competitive advantage.How do you harness data as an asset to prove that Digital strategy works? What are the elements that get the attention of senior leadership? What are the enablers?• Culture – Understanding Digital strategy & the importance of data and the freedom to experiment. “Failure is always an option” attitude• People – Knowledge, expertise, willingness to risk• Leadership – Empowerment, understanding, coaching, mentoring and risk taking• Purpose – Why do we do this?• Vision & strategy
Sakari will explain how EA data drives results at Talenom, one of the largest authorized accounting firms in Finland, using the CDO MIS. The Talenom CDO Management Information Systems (MIS) focuses on the management of information systems to provide efficiency and effectiveness of strategic decision making including:• What decisions C-level leaders need to make?• What different data elements they need to see?• How the operation is steered with the data? The Talenom Digital Services business unit, headed by Sakari Jorma, is operated via direct connections between MIS capabilities & Business operations. They operate in a conventional – one could argue in an “old fashioned business area”, of accounting. An average Accounting Company in Finland has around 5-7% level of digitalization when it comes to the handling of receipts, taxation, payroll data etc. So far one of Sakari’s main focuses has been automating and digitalizing Talenom’s main processes leading to the digitalization of materials as well. Today they are one of the leading digital accounting companies.You will hear:• How EA data helps them to do this?• What standardizations & governance elements are needed?• What is the role of Data warehouse, BI and MDM in this?
Fast Data: The Next Frontier of Big Data Rick van der Lans, R20/Consultancy
In the first stage of big data adoption, the focus was primarily on storing and analyzing massive amounts data. The focus was completely on volume. Currently, organizations have started to enter the second stage of big data: fast data. Fast data is about streaming massive amounts of data and analyzing that same data instantaneously. It’s the next frontier of big data. It’s especially the Internet of Things (IoT) that’s pushing fast data. The IoT is about connecting devices to devices across the Internet. The stream of data these intercommunicating devices can generate is massive. In these massive data streams valuable business insights can be hidden, deeply hidden. The business value of the IoT is in analyzing this data. Unfortunately, analyzing IoT data is not similar to analyzing enterprise data for which data warehouses can be developed and easy-to-use data visualization tools can be deployed. For example, IoT data is very cryptic data and to make sense of it, it has to be integrated with enterprise data residing in the enterprise data warehouse. Also, data has to be analyzed real-time, and sometimes even before it’s stored, and a reaction may be required instantly. It’s a new world. This keynote discusses the architectural aspects of the IoT, guidelines on how to adopt IoT, and how to integrate IoT with an existing business intelligence environment.
• How does fast data relate to the classic world of business intelligence and data warehousing?
• A new architecture is required for the IoT
• Technologies involved in analyzing the IoT data stream
• How to integrate IoT data with data from the enterprise data warehouse
• The challenge of reacting real-time on incoming IoT data
• What is the relationship between Big Data and the IoT?
Data Science and the Panama PapersMar Cabra, Editor, Data & Research UnitInternational Consortium of Investigative Journalists (ICIJ)
The trove of files that make up the Panama Papers is likely the largest dataset of leaked insider information in the history of journalism. Mar will discuss the unique challenges that ICIJ’s Data and Research Unit encountered in analyzing this data. The overall size of the data (2.6 terabytes, 11.5 million files), the variety of file types (from spreadsheets, emails and PDFs to obscure and old formats no longer in use), and the logistics of making it all securely searchable for more than 370 journalists around the world are just a few of the hurdles they faced over the course of the 12 month investigation.
Scaling out Data Operations in a Global Bank Alasdair Anderson EVP Data Engineering Nordea Bank Bert Oosterhof EMEA Field CTO Trifacta
Dr Richard Harmon Director, EMEA Financial Services Cloudera
The demand for data has never been higher and the supply provided by traditional EDW platforms is as constrained as it ever was. Many enterprises have realised that without leveraging the power of Big Data technology enterprises will fail to meet the demands of customers, executive and external regulators. In this presentation Alasdair Anderson, EVP Data Engineering Nordea Bank will discuss the evolution Data Architecture from EDW through Hadoop 1.0 to the Enterprise Data Hub. The Enterprise Data Hub now forms the data backbone of the bank providing data that support core regulatory, compliance and finance reporting.• What is an Enterprise Data Hub?• How is Business Data Operations supported on the Enterprise Data Hub?• How can change be executed on a scale out platform to deliver improved
data quality
Closing Keynote: You Can Take It With You Graeme SimsionInternational Best-Selling Novelist (and Former Data Modeller)
Graeme Simsion’s career has taken him from computer operator, to programmer, DBA, data modeller, data manager, IT strategist, consultancy manager, business facilitator and, more recently, Hollywood screenwriter and New York Times best-selling novelist. Graeme will talk about the generic skills in design, management and consulting that have helped him make the transitions and continue to be at the core of his work. You will learn:• The practices most critical to implementing BI / ED initiatives – and writing
a bestselling novel• The key strategies for winning support• The most valuable and portable skills to invest in
Group Booking Discount 2-3 Delegates 10 per cent 4-5 Delegates 20 per cent 6 + Delegates 25 per cent
Keynotes
View full conference programme on irmuk.co.uk/edbi20162
Strategic Change Leader - Business and Technology Transformation for the
Digital Age
12:10-13:40 Lunch, Exhibit and Perspective Sessions
12:40-13:05 Taming the Data Lake, Mark Pritchard, Denodo Data Lakes and Master Data Management, Michal Klaus, Ataccama
13:10-13:35 Data Governance - Slim and Simple, Tom Barta, Semanta Trillium Software - Session TBC
13:40-14:30 KEYNOTE: Fast Data: The Next Frontier of Big Data, Rick van der Lans, R20/Consultancy
14:35-15:25
“Little Data” - Gaining Sustainable Insight Through
Self-Service BI Jan Henderyckx
Inpuls
Agile Analytics - Bringing Data and Delivery Together
Rhys David Chief Technology Officer, Sonovate
How to Survive the CEO’s Trough of Disillusionment
with DataRoberto Maranca, Managing Director
Enterprise Data, GE Capital
Data Quality – A Different Perspective
Neil Storkey, Independent ConsultantPalash Banerjee, Associate Partner,
IBM
Architectures for Big Data Analytics
Markus Helfert Dublin City University
15:50- 16:40
Migrating our Enterprise DW from “Traditional” to Data
Vault BasedZoltan Csonka, Head of DW, Generali
Gabor Gollnhofer, DMS Consulting
Modernising Data Architectures Using Data
Virtualization for Agile Data Delivery
Dave Kay, Senior Data Consultant Zurich UK General Insurance
Data Governance as a Force Multiplier
Lt Col Mike Servaes Data Strategy British Army
From Data Blind to Data Funded: The IFC World Bank Group Story Gwen Thomas, Corporate Data Advocate Jennifer Trotsko, Head, Data Governance
Office Sana Al-Hajj, Manager, IFC World Bank
Panel Discussion: Riding the Elephant:
The Governance of Hadoop Environments
Moderator: Brian McKenna, Business Applications Editor, Computer Weekly
16:45- 17:05 Lightning Sessions - Four 5 minute sessions - What If Data...., Jan Henderyckx • Pie Charts Are Evil, Glen Bell • Speak Up and Thrive, Lee Edwards • There is No “Them”, Anthony Algmin
17:05-17:35 KEYNOTE: Data Science and the Panama Papers Mar Cabra, Editor, Data & Research Unit, International Consortium of Investigative Journalists (ICIJ)
17:35-18:30 Drinks Reception and Exhibits
9 NOVEMBER 2016 - Conference Day 2 & Exhibits
09:00-10:00 KEYNOTE: Scaling out Data Operations in a Global Bank Alasdair Anderson, EVP Data Engineering, Nordea Bank, Bert Oosterhof, EMEA Field CTO, Trifacta, Dr Richard Harmon, Director, Cloudera
DW/BI DW/BI Enterprise Data Enterprise Data Data Innovation
10:30-11:20 The DNA of a Surviving Business Intelligence Program
Pablo Sebastian Casullo BI Development and Strategy Lead
Merck Sharp & Dohme
Is Data Warehouse Automation a Necessity?
Rick van der Lans R20/Consultancy
Fostering Data Babies - Engaging a Younger
Generation of Information Professionals
Tony Mazzarella, Analytics Solutions Architect, Financial Industry & DAMA
Data Quality Distilled: An Essential Guide for Data
Management Professionals Jon Evans
EQUILLIAN
Building a Data Infrastructure for a Smart City
Rutger Rienks Program Manager City of Amsterdam
11:25-12:15 The Trials, Tribulations and Successes of Building an
Enterprise Customer Data Warehouse
Sophie Holland, Royal Mail
Integrating Big Data Analytics into a Self-Service BI
Environment Mike Ferguson
Intelligent Business Strategies
Become a Data SuperheroRob Zagey
Senior BI Analyst STANLIB
Expert Panel: Building your Career in Data
Moderator: Mike Simons, Associate Editor for CIO.co.uk,
ComputerworldUK and Techworld, IDG
MDM in Financial Institutions - and What’s Next?
Lukas Mazanek, Head of Data & Information Competence Center,
Raiffeisenbank
12:15-13:45 Lunch, Exhibit and Perspective Sessions
12:45-13:10 Create BI Success with Effective Dashboards Carl Edwards, Yellowfin
DAMA Int & the DAMA Chapters - A Perspective, Sue Geuens and Chris Bradley, DAMA The 5 Must Do’s for Guaranteed Data Governance Success, Patrick Dewald & Darius Clayton, Diaku
13:45-14:35 How to Make Business Tools People Want to Use and Actually Use Well: A Case Study in BI Tool
Design from Zipcar Will Sprunt, Head of Analytics
Zipcar International
Knowing What to Do By Using Data from the Future
Håkan Edvinsson Informed Decisions
The Journey to a Data-Driven Culture Ian Wallis
Head of Data, Analytics & Insight Defence Infrastructure
Organisation
From Small Experiments to Viable Data Governance
Petr Podany Head of Data & Analytics
Sberbank CZ
The Data Renaissance: Leading Your Business to the Modern
Age Anthony Algmin
Uturn Data Solutions
14:40-15:30
BI Case Study Speaker / Session TBC
Taking the Internet of Things Beyond Data to Actionable
Insights Hylke Peek, The Backbone Niels Naglé, Info Support
The Quality in Master Data Quality
Dana Julinschi Master Data Governance & Projects Manager
Friesland Campina
Ethics in Information Management Practices
Katherine O’Keefe, Data Governance & Privacy Consultant
Castlebridge
Open Data I Love It! But Not My Data, It’s Special
Lisa Allen National Data Integrity Manager
Environment Agency
15:50-16:50 CLOSING KEYNOTE: You Can Take It With You Graeme Simsion, International Best-Selling Novelist (and Former Data Modeller)
Age
nda
10 NOVEMBER 2016 - Full Day Workshops
DW/BI Enterprise Data Enterprise Data Enterprise Data
09:00-16:30
Maximising Business Value Using Predictive Analytics, Self-Service and
Collaborative BIMike Ferguson
Intelligent Business Strategies
Making Enterprise Data Quality a RealityNigel Turner
Global Data Strategy
Successful Implementation of a Master Data Management Programme
Malcolm Chisholm First San Francisco Partners
Preparation for the Certified Data Management Professional
(CDMP) Exams Leading to CertificationChris Bradley
Data Management Advisors Ltd
View full conference programme on irmuk.co.uk/edbi20164
Half Day Workshops - 7 November
BUSINESS INTELLIGENCE
Designing the Logical Data WarehouseRick van der Lans, R20/Consultancy
The classic data warehouse architecture has had a long and successful run, but we’re starting to stretch its abilities to the limit. The logical data warehouse is a modern alternative. It offers several practical benefits, including that it’s more agile, it makes adoption of big data easier and more seamless, it allows a management the self-service BI component, it can more easily exploit new data storage technologies such as Hadoop and NoSQL, and is more suited for operational BI applications. Mature technology in the form of data virtualization servers exists to develop a logical data warehouse. Products from Cisco, Denodo, and RedHat, have proven that large BI systems can be developed using data virtualization. This workshop explains the architecture of a logical data warehouse and discusses numerous tips, tricks, and guidelines for designing and developing one, and a structured approach for migrating to a logical data warehouse is taught.
The Key to Big Data Modelling: CollaborationLen Silverston, President, Universal Data Models
Some claim that in the age of Big Data, data modelling is less important or even not needed. However, with the increased complexity of the data landscape, it is actually more important to incorporate data modelling to understand the nature of the data and how they are interrelated. To do this effectively, our approaches to data modelling need to adapt to this complex environment. One of the key data modelling issues is how to foster collaboration between new groups, such as data scientists, and traditional data management groups. There are often different paradigms, and yet it is critical to have a common understanding of data and semantics between different parts of an organization. In this presentation, Len Silverston will discuss:• How Big Data has changed the enterprise
landscape and affected data modelling• How to conduct data modelling in a more ‘agile’
way for Big Data environments• How to collaborate effectively within an
organization, even with very different perspectives
Data Science in ActionJos van Dongen, Principal Consultant, Tholis Consulting
Data Science has been called ‘The Sexiest Job in the 21st Century’ and is a hot topic in the world of analytics. It promises breakthrough insights and skyrocketing ROI percentages, delivered by teams of extremely smart people using state of the art technology. At least, that’s what analyst firms and trade magazines want us to believe. Reality is that many organisations are just starting out with their first ‘Big Data Labs’ or are struggling to move beyond technology oriented proof of concepts. The challenge is how to put the business in the driver’s seat and use technology as an enabler and not for the sake of technology alone. This session will look at both concepts as well as practical approaches in moving towards becoming a data and analytics driven organisation. The following topics will be
covered:• Concepts: what is Data Science and how is it
different from BI?• Use Cases: Data Science success stories from a
variety of sources• Skills: can my BI team become a Data Science
team? (and how?)• Process: how do you facilitate Data Science
within your organisation?• Tools & Technology: what are the technical
requirements for a successful Data Science team?After this session you will be able to look beyond the hype and will have a good understanding of the benefits of adopting data science within your organisation.
Introducing Agile Business Intelligence Sustainably: Implement the Right Building Blocks in the Right Order Raphael Branger, Senior BI Solution Architect, IT-Logix AG
“We now do Agile BI too” is often heard in todays’ BI community. But can you really “create” agile in Business Intelligence projects? This workshop shows that Agile BI doesn’t necessarily start with the introduction of an iterative project approach. An organisation is well advised to establish first the necessary foundations in regards to organisation, business and technology in order to become capable of an iterative, incremental project approach. In this workshop you will learn, which building blocks you need to consider. In addition you will see what a meaningful sequence to these building blocks is. Selected aspects like test automation, BI specific design patterns as well as the Disciplined Agile Framework will be explained in more and practical details. Top 3 Take Aways:• Identify what building blocks are necessary to
introduce Agile BI in a sustainable way• Learn about the sequence of implementation of
the building blocks for Agile BI• Become aware of typical trap doors when
starting Agile BI
Modeling for SQL and NoSQLKenneth Hansen, Managing Consultant, Analyticdomain Ltd
This workshop will be a sharing of experiences and lessons learned in the trenches of projects for Lufthansa Airlines with references to previous projects with a Telco and a shipping Company. Data Models are seen by many as an unnecessary legacy but those based on Conceptual and Logical models offer flexibility and future proofing” - they are key to integrating and scaling data and queries in both Relational and NoSQL Schemas and future proofing. For the Agile organisation the models provide a framework that reduces technical debt and the concerns over duplication and lack of consistent progress in developing enterprise capabilities. Generic Industry Data Models can be valuable but there is much more to modelling than producing a diagram of entities and relationships. Implementation requires generic structures are validated and customised and involves alignment of all stakeholders and team members - a process that is fraught with pitfalls. The speaker will share experiences and recommend key best practices in the conference session including:
• Successful Conceptual Models can and should be
memorised as drivers for detailed models - larger models should be abstracted.
• Conceptual Models must be agreed at enterprise level by the business leaders and enterprise architects and then serve as the cornerstones of Logical Models.
• Successful Conceptual and Logical Data Models establish a common language for the Enterprise, Data Governance and all Analytics
In the 3 hour workshop Kenneth will detail the process recommended for validation, customisation and implementation of a generic industry LDM .
Getting Ready for the General Data Protection Regulation – An EIM2.0™ ApproachDaragh O Brien, Managing Director, Castlebridge
The General Data Protection Regulation comes into effect on the 25th May 2018. While at the core, the fundamental objectives remain the same, the GDPR introduces a number of significant changes for organisation with regards to how they need to plan for, manage, govern, and apply data that relates to identified or identifiable individuals. The implications of GDPR are far reaching as it has set a new benchmark for global data privacy standards, not least with its extra territorial effect that means non EU-based organisations processing data of EU residents will have to comply. In this intensive session, internationally recognised expert Daragh O Brien will:
• Provide delegates with a pragmatic overview of the key provisions of the GDPR
• Explain the penalties and enforcement frameworks that will exist under GDPR (and which are being introduced already in certain EU Member States)
• Outline the impact of recent EU Court of Justice rulings on Data Privacy laws in the EU and elsewhere, and how that impacts the governance, planning, and management of information in your organisations
• Discuss the other changes in EU Data Privacy laws that are emerging, and the impact on international data privacy regulation
• Explore how agile principles and methods can be applied to getting ready for GDPR
• Map out how frameworks such as the DMBOK Wheel and the Zachman Framework, and methodologies and principles from Data Governance and Data Protection can help with implementation of GDPR, including the execution of Privacy Impact Assessments
• Introduce the concept of EIM2.0™ – Ethical Information Management and how this can support and enable GDPR governance, particularly in the context of the Risk based model for Regulation
ENTERPRISE DATA
Master Data Management William McKnight, Consultant, McKnight Consulting Group
This workshop provides a practical guide to implementing successful MDM from experience. It covers all the aspects of MDM, from justification to architecture to data management and project management using agile principles. This class
View full conference programme on irmuk.co.uk/edbi2016 5
Half Day Workshops - 7 November
gives the common process, organisational and architectural focus for building strategies and implementing master data management programs such as those that have consistently, for many years, improved the productivity and performance for clients including global giants.• How MDM provides benefits to an organisation
and how to justify an MDM project• The various architectural styles of MDM• What MDM provides for hierarchy management
and data governance• How to go to market for an MDM tool• All the roles and responsibilities on an MDM
project• How to manage the organisational change that
occurs with MDM projects
Carrying out a Data / Information Maturity AssessmentSue Geuens, Head: Data Standards & Best Practice, Barclays & President DAMA International
Knowing how mature your organization is and how ready it may be for a data and information management program should be high on your list of priorities. After all, we have all heard “you don’t know what you don’t know” before, haven’t we? But (and this is the big one), how do you assess this maturity? Is there a magic bullet, a special methodology or a trusted approach that everyone uses? One that you can go and buy somewhere? Sue says she doesn’t know of one specific one and has been working with clients over a number of years trying to perform that miracle. Sometimes it has worked and sometimes not. However, challenges are her bread and butter!
Join Sue on a journey to assess your maturity for Data and Information. But be prepared: there is work to be done and you will walk away at the end of the workshop with a maturity assessment of your organization (or if you are a consultant with that of a client of your choice!). You will also walk away knowing that you can do this assessment again and again and again, over as long a period as you want to. This will, of course, allow you to measure your success! Please bring along a PC, a tablet, or - if all else fails - a Smartphone. You will be taking the assessment.• How important doing a regular maturity
assessment is• Take home the actual tool to do this• Some new skills on how to get people to do the
assessment
Getting Our Heads into the Clouds: Infinitely Scalable Data ManagementAnthony Algmin, Chief Data Officer, Uturn Data Solutions
The cloud is not the future of enterprise computing: it’s the NOW of enterprise computing. We are in the midst of a data awareness renaissance, and our organizations are demanding that we build analytics capabilities to drive future success. Cloud technologies are part of the answer, but to fully respond to these challenges we need to bring new mindsets and techniques to data management. It’s up to us data professionals to bring these capabilities to our businesses. If your business is not already there, it needs to be. Come to this session to learn how to get to the cloud, and how our data management practices must evolve to harness the power.
This session will cover a pragmatic foundational
perspective on hot data terms you have heard about, like:
• Big Data - a relative scale challenge that has always existed
• Data Lakes - optimizing data structuring energy across place, time, and purpose
• The Cloud - forget what you knew about it three years ago
• Private Cloud - like buying an airplane versus flying commercial
• Internet of Things - this will make current Big Data scale laughable in the next few years
• Data Science - a capability far too important to be left entirely to data scientists
• Why the cloud makes some new things possible, many things easier, and a few things much harder – and how we need to adapt our data management practices in response
• Why business impact is the only thing that really matters
• What all this means for business as usual, and how to build a high-performance organization driven by data in the cloud.
What is Quality Data and Why Do We Need It? Sophie Angenot, Managing Partner, QuaData
Even in companies where some people are already convinced, selling the idea of investing in something that looks as trivial as data quality, is not easy. So, where do you start? How can you measure quality with no or very little tooling at hand? What arguments can you use towards your stakeholders? And once your stakeholders are on board, where do you start? Sophie will give you some examples of companies that started from scratch, and will go through a typical DQ-roadmap with solutions in the 3 aspects that impact the quality of your data: people, governance and technology. She’ll also bring some of QuaData’s surveys so you can assess the situation of your own company. You will leave this workshop with at least one feasible first or next step for your own company. And lots of them to build your roadmap to the right level of data quality. You will you learn:
• How to convince your stakeholders of the importance of DQ
• How to gather basic measurements about the quality of your data
• Where to start and what to consider in your roadmap
From Vision to Capabilities: Effective Building Blocks for Information Centric Organisations Jan Henderyckx, Managing Partner, Inpuls
Keeping control over the design- and architecture activities that are performed within your organisation without creating a top heavy governance organisation is quite a challenge. Justifying why certain choices have been made and come up with the proper reasons to invest in a particular solution can be quite tricky. The latter is often performed in an ad-hoc and unstructured way.
One of the current hypes is the concept of capabilities which can be loosely defined as “things that you should be able to do”. The idea behind the capability approach makes sense as it starts from the assumption that when you describe what and why you want to perform you end-up with the
right mix to reach your objectives. This brings us to the more fundamental question of the underlying drivers. The workshop will take you through the different steps of translating a vision into policies, principles and standards that guide your reference architectures and blueprints. We will cover the framework that connects all the different elements into a practical toolkit that underpins you reference architecture and transforms standalone statements such as “information is an asset” into useable steering of your designs and architecture.
• Understanding the policy framework concept
• Linking vision to actions
• Outcome driven capabilities
• Reference architectures for common use cases, MDM, Analytics, BI, Data Quality
Creating Better Business Diagrams Glen Bell, Director, Visual Explanations
Data management professionals need to create diagrams to explain concepts. Unlike written communication, where everyone is taught grammar and how to write clearly, there is almost no training in creating effective diagrams for business communication.
This workshop explains a set of diagramming techniques based on Gestalt principles. The focus is to create diagrams that are easily understood. By the end of the workshop you will be able to formally assess a diagram and understand how to improve it to make its message clear and compelling. The same techniques will also be applied to tabular information to improve its clarity. The workshop has a strong emphasis on doing exercises to re-inforce the concepts. No drawing skills are required.
• Techniques for assessing and improving business diagrams
• Understand how to apply these techniques to other communication areas such as tables of data
• Ensuring the communications resonates with the target audience
All Roads Lead to Data Funding Gwen Thomas, Corporate Data Advocate Jennifer Trotsko, Head, Data Governance Office, Sana Al-Hajj, Manager, IFC World Bank Group
Many Enterprise Data Management programs struggle for funding, especially for work that doesn’t fit neatly into IT Projects. And yet, in just 2 ½ years, IFC (the private sector arm of the World Bank Group), evolved from “invisible” data needs to a well-funded, interdependent set of projects and work plans. In this highly-interactive workshop, the team behind the funding strategy coaches you through the process of finding your own path to increased funding. The presentation explores:• 5 funding models, and when each might be
deployed• Stakeholder analysis, and getting “a seat at the
table” for the right people in the right venues
“This event never fails to enable me to connect with people who I can learn from and who can re-energise me in Data Management.”Andy Moore, Rolls Royce
“Great opportunity to validate my views and to learn from others.”Garry Manser, Head of Data Governance, Visa Europe
“Great conference, the best event in Data Management! Excellent speakers and very interesting content.”Ana Teresa Szmoes, Caixa Geral de Depósitos
“Excellent event, would thoroughly recommend it to all data professionals. Would actively encourage potential delegates to attend pre-conference sessions, very informative sessions. The opportunity to listen and interact with so many like minded data professionals in one place.”Jimmy McGrath, Information Development and Improvement Manager, Care Quality Commission
“Second time at this Conference, will be back but next time with my team!”Derek Lennox, Data Governance Manager, National Australia Bank Group
“Good variety, good to have different views on same subjects. Informative, can now “join the dots” on capabilities for my organisation. Plenty of information, lots of food for thought.”Teresa Bateman, Solution Architect, Tesco Plc
“I have greatly enjoyed this event. The material is very useful to me. I enjoyed discussing data management issues with like-minded professionals.”Rhonda Freeman, Autotrader
“Very good event, well organised and relevant particularly virtualisation, cloud and data strategy sessions.”Gerrard Deegan, Enterprise Data Architect, Ministry of Defence
“Great way to learn best practices, gain new insights and get ideas for change in your own organisation.”Weird van der Kooi, Sr. Data Manager, Nuon Vattenfall
“An excellent event which really helped me understand the new trends in DW/BI, Data management and Information System Quality. I will recommend this event to my fellow professionals.”Sheraz Mustaq, Saudi Aramco
“I would attend this event over and over again. It’s worth all the effort! I must commend the organiser for a well done job. So far, this event marks the best of conference experiences in the past 10 years.”Abraham Afolabi, Data Manager, EC Harris LLP
“I was glad to find like minded professionals confirm several decisions I have made. Also glad to find several thought provoking and extremely useful nuggets that I can take back with me.” Overall value of event - 10/10.Chris Duffield, Principal Developer, Transport for London
“A very enjoyable and useful event. This is the first conference I have attended but I would certainly like to attend further conferences. The venue and staff were excellent and it was very well organised.”David Jordan, Data Analyst, Land Registry
“The event was very energising... seeing other companies on the same journey, with the same issues was good to see. Some good take always... nuggets that will be employed back at work. Enjoyable event.”David West, Group Data Architect, Barclays Bank
“Extremely well organized, lectures were thought provoking. Many ideas I will take back to my organization. A lot more I now want to read about. I will recommend this conference to more business units next year. Thoroughly enjoyed it!”Neil Shah, Information & Data Risk Analyst, Capital One Bank
• A Three Pillar Model that brings visibility to work that business and IT stakeholders may have been blind to
• How and when to involve Enterprise Architecture, Information Security, and BI
• The value of inserting data reviewers into IT Governance, Lifecycle Management, and IT Portfolio Management
Building Professional Competencies for Information Management PractitionersChris Bradley, Information Strategist, Data Management Advisors Ltd
Considering a career in Information Management? Already well established in the field? Want to build an information management practice in your organisation? It’s not only the “Information Management” skills that are essential. This workshop will address the key issues of:• What key capabilities are necessary (and
desirable) for IM professionals• What behaviours and attitudes should be
exhibited• What are the roles necessary in a successful
Information Management practice• What are the skills and skill levels required to
fulfil those roles,• What are the core services necessary to
permeate an Information Management practice & how should these mature, and
• Does certification help?
BIG DATA
Big Data Platform Fundamentals – New Infrastructure in Your Analytical EcosystemMike Ferguson, Intelligent Business Strategies
This session provides an introduction to core platforms for big data analytics and walks through the main components.• The new multi-platform analytical ecosystem• New platforms in the logical data warehouse• An introduction to Hadoop and the Hadoop
Stack• What is HDFS, MapReduce, Pig & Hive?• What is Apache Spark? –in-memory massively
parallel analytics• Data Warehouse offload – ETL on Hadoop and
Spark• Accessing Hadoop data using SQL on Hadoop• Security on Hadoop• The Big Data Marketplace Hadoop distributions Big Data Appliances Streaming Analytics NoSQL databases• The Cloud deployment options
• Creating a multi-platform analytical ecosystem
Big Data Technology and Use CasesWilliam McKnight, McKnight Consulting Group
This workshop provides an approach for storing, managing and accessing data of very high volumes, variety or complexity. Storing large volumes of data from a large variety of data sources in traditional relational data stores is cost-prohibitive. And regular data modelling approaches and statistical tools cannot handle data structures with such high complexity. This seminar discusses use cases and new types of data management systems based on Hadoop and NoSQL database management systems and alternative programming models and access methods.• Big Data Overview and Common Themes• The main characteristics of Hadoop and NoSQL
databases• Differences between a distributed database and
relational databases• NoSQL data models: key-value, columnar,
document• Use cases for big data, with real-world examples
from organizations in production today• The placement of big data in information
architecture• Scale up versus scale out• MapReduce and Spark• Graph Stores: All about Relationships
• Enablers for big data in the enterprise
View full conference programme on irmuk.co.uk/edbi20166
View full conference programme on irmuk.co.uk/edbi2016 7
Full Day Workshops - 10 November
Maximising Business Value Using Predictive Analytics, Self-Service and Collaborative BI Mike Ferguson, Intelligent Business Strategies
An Overview of Predictive Analytics and Machine Learning
As we move into the era of smart business, looking back in time is not enough to make good decisions. Companies have to also model the future to forecast and predict so that they can anticipate problems and act in a timely manner to compete. Predictive analytics is a therefore a key part of any BI initiative and should be integrated into analysis, reporting and dashboards. This session introduces predictive analytics and how shows how it can be used in analysis and in business optimisation
• What are predictive analytics?
• Technologies and methodologies developing predictive analytical models
• Using supervised learning to develop predictive models for automatic classification
• Clustering data using unsupervised learning algorithms
• Deploying predictive analytical models in analytical databases
• Implementing predictive analytics in-Hadoop
• Accessing in Hadoop machine learning algorithms from data mining tools
• Integrating predictive analytics with event stream processing for automated analysis of high velocity events
Self-Service Data Discovery and Visualisation Tools
Self-service Data Discovery and Visualisation tools are frequently sold into business departments so that local business analysts can start building their own BI applications without having to wait for IT. This means that development often starts without any IT guidance and quickly spreads to other parts of the business with little thought for integration or re-use. The result is that inconsistency and chaos can quickly set in. This session looks at best practices in deploying Self-service Data Discovery and Visualisation tools to maximise business benefit in existing BI/DW environments
• What are Self-service Data Discovery and Visualisation tools?
• Interactive analysis and automatic charting using in-memory data
• The Self-service Data Discovery and Visualisation tools marketplace e.g. Qlik Sense, Tableau, Tibco Spotfire, SAP Lumira, Information Builders, SAS Visual Analytics, Yellowfin
• Accessing predictive analytics from self-service BI tools
• Accessing Big Data from self-service BI tools using SQL on Hadoop
• Best practice steps in deploying self-service BI applications
Sharing BI Content through Collaborative BI and Storytelling
One of the key requirements in the smart enterprise is being able to easily access and share BI content with others both inside and outside the enterprise. To make this possible, BI platforms need to simplify user interfaces while adding collaborative and storey telling capabilities. This session looks at how collaborative computing and BI come together to
facilitate easier sharing and communication of insight. • The challenge to older hierarchical ways of
working• The Facebook revolution – New technologies
for enterprise collaboration• Why use enterprise collaboration and social
computing?• Analytical communities in the enterprise• Decision making at strategic, tactical and
operational levels• Why Collaborative BI? • Requirements for collaborative and social BI• Types of user - information producers vs.
information consumers• Collaborative BI authoring for information
producers • Using collaborative BI for joint decision making
and knowledge sharing • Empowering the masses to create, share, search
and collaborate over BI and related content• Collaborative BI technologies, e.g. Antivia, IBM
Cognos Business Insight, LyzaSoft, , Panorama Necto, Tableau, SAP Lumira, Yellowfin
• Using portals together with collaborative BI
Mobile BI – Extending the Reach to New Devices
Now that mobile devices have made great strides in their rich user interfaces, one of the hottest new areas is business intelligence is Mobile BI. This session looks at how modern mobile devices can now connect to BI platforms to access insight from inside or outside the enterprise. It also looks at how dis-connected users are now supported and how mobile workers can participate in collaborative BI environments and act on business insight to improve business performance.
• Popular Mobile BI use cases
• What should be in a Mobile BI Strategy
• Types of BI user and mobile device usage
• How have BI platforms been ex- tended to support mobile BI?
• The mobile BI marketplace
• Authoring mobile BI content
• Mobile BI Security – what to look for
• Evaluating mobile BI for the information consumer
• Integrating mobile BI with other applications and services
Making Enterprise Data Quality a Reality Nigel Turner, Principal Information Management Consultant EMEA, Global Data Strategy
Many organisations are recognising that tackling chronic data quality (DQ) problems requires more than a series of tactical, one off improvement projects. By their nature many DQ issues extend across and often beyond an organisation. So the only way to address them is through an enterprise wide programme of data governance and DQ improvement activities embracing people, process and technology. This requires very different skills and approaches from those needed on many traditional DQ projects.
If you attend this workshop you will leave more ready and able to make the case for and deliver enterprise wide data governance & DQ across your organisation. This highly interactive workshop will also give you the opportunity to tackle the problems of a fictional (but highly realistic) company who are experiencing end to end data quality
& data governance challenges. Attending this workshop will enable you to practise some of the techniques taught in a safe, fun environment before trying them out for real in your own organisations.
The workshop will draw on the extensive personal knowledge & experience of Global Data Strategy’s Nigel Turner who has helped to initiate & implement enterprise DQ and data governance in major companies including BT Group, British Gas, Intel and many other organisations. The approaches outlined in this session really do work.
• What differentiates enterprise DQ from traditional project based DQ approaches
• How to take the first steps in enterprise DQ
• Applying a practical DQ & data governance framework
• Making the case for investment in DQ and data governance
• How to deliver the benefits – people, process & technology
• Real life case studies – key do’s and don’ts
• Practice case study – getting enterprise DQ off the ground in a hotel chain
• Key lessons learned and pointers for success
Successful Implementation of a Master Data Management Programme Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners
This workshop focuses on the key elements of an MDM programme that are needed for overall success. It gives practical recommendations while at the same time providing a conceptual understanding of what is involved in these recommendations. Both governance and management are covered, and emphasis is placed in how MDM fits into a larger business strategy and architectural setting. MDM programmes are rapidly evolving as new data possibilities emerge and enterprises demand more from MDM than they have previously. These emerging challenges of MDM are addressed in detail.
• What is Master Data, how does it differ from other classes of data?• What the practical implications
are for governing and managing Master Data.
• How do you control scope on your MDM program
• Dealing with business justification, and managing expectations
• How strategies like customer-centricity require MDM
• How new MDM-driven business models are emerging, and their implications
• Architectures for MDM• The traditional MDM architectures
(hubs) and their pro’s and con’s• The separation of Master Data creation
and distribution
• Deciding the scope of Master Data, particularly static versus profile data
• What MDM vendors can do for you and what they cannot
• The need to put MDM into a bigger architectural picture to achieve business results
• How to work with the business to be successful in MDM
• Examples of how different Master Data entities require different overall approaches, and the implications for an MDM program.
• How to deal with the Operations business community and meet their needs
• How to deal with the Analytical business community and meet their needs
• Getting governance needed for MDM into the business
• Dealing with data integration, changed data capture, and data quality successfully
• What is the right approach to data integration?
• How to implement continuous production data quality monitoring
• Inferring history, versus capturing historical events, and how to store this
• The role of business rules in driving MDM
• Mastering Master Data Semantics• Dealing with the different “types” of
Customer, Financial Instrument, etc.• Capturing knowledge of the Master
Data• The vital role of reference data in
MDM• The roles of generic data models and
specific data abstraction layers
• Emerging Areas in MDM• Dealing with legal, privacy, and
compliance issues of Master Data• Sourcing Master Data from outside
the enterprise• Social Media fraud• The role of Big Data
Preparation for the Certified Data Management Professional (CDMP) Certification Exams Chris Bradley, Information Strategist, Data Management Advisors Ltd, DAMA CDMP Fellow & President, DAMA UK
This full day workshop covers an overview of the process, tips and techniques of successful CDMP exam taking. In this interactive and informative session, you will learn:
• What is the CDMP certification process
• The DAMA-DMBOK & CDMP data exams alignment
• What topics comprise each exam’s body of knowledge
• Concepts and terms used in the CDMP exams• A Self-assessment of your knowledge and skill
through taking the sample exams
The schedule for the day will be as follows:
09:00-12:15: Workshop Preparation for the Certified Data Management Professional (CDMP) Exams
See the conference website for further details about the CDMP Certification and Exams
BUSINESS INTELLIGENCE
CASE STUDIES
Agile Analytics - Bringing Data and Delivery TogetherRhys David, Chief Technology Officer, Sonovate
How many times have we heard that ‘data is important’, ‘data is a strategic asset’? Yes, a lot. Data is incredibly important but even more important is what you do with it. Gone are the days where our clever people spend weeks doing stuff with data and then the business decide to do something with it. It’s just too slow and by the time you have decided to use it, the world has moved on. Organisations must change their thinking and culture before becoming a data driven organisation. This session will explore how Rhys has implemented this and it how it can deliver significant value, quickly. What will delegates take-away:
• How to embed data/analytics within the decision making process
• How to bring delivery and data together
• What skills do your business need to leverage data/Business model dependant
Data Management, Analytics and People – An Eternal Golden BraidPeter Thomas, Head Of Data Management Insurance
The role of Data Management is often shown within a pyramid with analytical techniques, be these Statistical Modelling, Data Visualisation, Big Data or Business Intelligence at the top, supported by a much larger foundational areas of Data Strategy, Data Processes and Information Architecture. This view has many merits, but also two flaws. First it omits an important factor in adding value: people and cultural change. Second these three areas can be thought of as mutually reinforcing rather than as foundational and apex activities. I believe that that the leverage of data to yield information, provide insights and drive action is best achieved via interplay between these three equally important areas. Attendees will learn:
• The value of making Data Management more people-centric
• Three mutually reinforcing areas are stronger than a pyramid structure
• What bringing these three areas together means in practice
The DNA of a Surviving Business Intelligence ProgramPablo Sebastian Casullo, BI Development and Strategy Lead for Latin America, Merck Sharp & Dohme
In this presentation you will gain insight about what the “DNA” is of this real and current “Surviving” Business Intelligence Program. From conception to full production operation and evolution. Challenges. How over a ten plus year period of time, a long term program needs to adapt and evolve to survive. Business needs, architectural trends, Business Intelligence paradigms, technologies and egos, conform “corporate selective pressure” and remain a constant threat to survival. Pablo will describe how a regional Business Intelligence program
evolved from “wishful thinking” to becoming a critical and inevitable gear of the decision making process throughout the whole Latin America region (and beyond).
The DNA of this surviving BI Program:
• A clear vision (and strategy)
• Great Business sponsors to enable business value opportunities and grow the right roots
• Create and Deliver quantifiable value on every iteration with extreme focus
Modernising Data Architectures Using Data Virtualization for Agile Data Delivery Dave Kay, Senior Data Consultant, Zurich UK General Insurance
In this case study Dave will provide a profile of the global insurer Zurich and it’s status in the market. He will then describe the many challenges and threats it is facing in the Insurance market which means that it must respond at pace, which is a challenge for any large traditional insurance provider. Dave will explain how Zurich needs to rapidly deploy existing data assets and leverage new sources. He will show how we have achieved this with a modern data architecture which strongly leverages data virtualization. Key takeaways are:
• Explaining how the critical business challenges being faced by a large insurance company are mostly all about data
• Providing a detailed explanation of at least one case study on how we are solving that
• Explaining how this initially tactical use case(s) can provide a strategic way forward to modernising a data architecture
The Trials, Tribulations and Successes of Building an Enterprise Customer Data Warehouse Sophie Holland, Royal Mail
This session focuses on all the aspects to consider when building an Enterprise Data Warehouse. Sophie Holland will provide guidance on writing the business case, choosing the right infrastructure, and bringing the data warehouse to life after it has gone live to get the best use out of it in your company. Sophie will also talk about her experience of doing this at News UK and the challenges faced whilst getting a new CEO and a change in company strategy, along with what benefits were realised. News UK has made a significant commitment to put data and customer information at the heart of its business. In 2015 News UK implemented cloud technology tools for the Enterprise Data Warehouse and Campaign Management capability in house for the first time, removing its reliance on a third party, and owning IP.
• Getting approval for a data warehouse project in your organisation
• Business benefits of a data warehouse
• Lessons learned
View full conference programme on irmuk.co.uk/edbi20168
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Conference Sessions
The Benefits of a Data Virtualisation Solution: from Data Vault to SuperNova and Beyond Jos Kuiper, IT Enterprise Architect, Volkswagen Pon Financial Services
How can we improve agility in preparing data for end-users and for information products, like reports, dashboards etc.? For this purpose a proof of concept with a data virtualization solution was performed. Jos investigated the benefits of a data virtualisation solution on top of a Data Vault Data Warehouse. In this proof of concept also the capability of the data virtualization solution to combine historic data, stored in the Data Vault, with live data stored in back-office systems, was subject of investigation. In this presentation there will also be a brief introduction to the data modelling methods Data Vault and SuperNova. Key take aways:
• The benefits of a data virtualisation solution.
• The fit of data virtualization in a BI/DWH architecture.
• Unexpected benefits…..
Migrating our Enterprise DW from “Traditional” to Data Vault BasedZoltan Csonka, Head of DW, Generali Gabor Gollnhofer, Principal Consultant, DMS Consulting
Generali Hungary built its first Data Warehouse more than 15 years ago. Since then they have changed/reorganized its major parts three times. Because of changes in the internal & external environment they had to change their ETL tool (again). Last year they decided to do a complete reorganisation including their ETL & modelling tools, development processes and to move to Data Vault based modelling. Of course, they had to do this in a short time period with limited internal & external staff. The old and new DW had to work together, so that the major processes could be migrated one-by-one. In the session we will share our experience on EDW migration, specifically:• Why we had to move from our existing
architecture & why we’ve chosen to use Data Vault
• What were the pain points, pitfalls and solutions• What are the results & what we’ve learnt during
this project
How to Make Business Tools People Want to Use and Actually Use Well: a Case Study in BI Tool Design from ZipcarWill Sprunt, Head of Analytics, Zipcar International
Zipcar has a lot of data and people want to use it - what you wouldn’t expect is that this can be a problem. When everyone individually asks their questions and expects a report or tool to be developed from it you don’t always end up with more understanding or the real world, more agreement on what is really happening or more engagement with drawing insight from the data. If you aren’t careful you can end up with a proliferation of data without clear structure and confused end users wondering how it all fits together. This session will demonstrate a methodology we use in Zipcar based on questions and flow to determine how to build tools for understanding the business through data and will invite discussion on other methods that can be used to manage a growing BI and insight tool set.
BEST PRACTICE
Strategies for Consolidating Enterprise Data Warehouses and Data Marts into a Single PlatformWilliam McKnight, Consultant, McKnight Consulting Group
As companies grow in their realization of the value of information as a strategic asset, a re-evaluation of information architecture maturity and capabilities becomes essential. This has led many to corral their unwieldy, expensive environment into a more manageable and cost-effective infrastructure that produces the elusive bankable company numbers and metrics. During this session, industry expert William McKnight, will highlight key strategies leading edge companies have adopted to reduce the complexity of their data warehouse environment for maximum efficiency.
• Inefficient Information Architecture
• Methods of Data Mart Consolidation
• Many data marts, 1 data warehouse
• Many data warehouses, 1 data warehouse
• Choosing survival systems
• Keys to Data Mart Consolidation Success
Gaining Business Value from The Internet of Things (IoT) and Critical Human FactorsLen Silverston, President, Universal Data Models
Realizing business value from the coming wave of Internet of Things (IoT) capabilities can be confusing when it affects your core business, adds new opportunities for expansion, and taxes your abilities to manage complex architectures. Understand how to formulate a winning approach that covers the bases, giving you the ability to execute and generate value and competitiveness in this new arena. This session focuses on the most important factors for success in IoT, namely: how to link IoT to meaningful business objectives to create business value; how to maneuver through the politics; how to develop a strategy that makes sense; and how to handle the inevitable scenarios, challenges, and conflicts that occur in this environment.
Come to this session and understand the critical factors, take back tools and frameworks regarding organizational management in IoT, and learn how to succeed in a field with the potential to disrupt all the current business models as we know them. You Will Learn:
• The five key areas to focus on immediately in preparing for IoT
• A framework to understand business needs, along with how it can help prioritize your needs
• How to start formulating a strategy for IoT
• How to address key issues in IoT such as privacy, security, and control using a trust framework
• What inevitably happens in these types of efforts and how to address situations using proven and effective conflict management models
Having a data lab up and running does not equal a sustainable integration into the operational and strategic fabric an organisation. Big Data and Analytics are omni-present in many organisations and the mantra of statistical relevance is often used as an excuse for neglecting “little” data. Even if all your big data is accessible in your data lake you still need to understand what the data relates to. Without context you just have a huge pile of data points.
The little data, data that has a life cycle and that describes the related business concepts, will provide the context that allows you to obtain actionable insights. Proper management of the life-cycle of the business entities and their relationships will therefore give a significant boost to your business outcomes. Unfortunately, many master - and reference data management (MDM/RDM) projects are not providing the benefits that are anticipated.
This session will give you practical advice to setup your data management and information governance in such a way that you can get maximum value out of your data without increasing your liabilities.• Setting the scene: Defining a sustainable
Information centric organisation• Drowning in the data lake or having
a breach? Information and Data Governance as a safeguard
• MDM and RDM design principles • Bringing the proper life-cycle
management into your organisation?• Architecting the conform dimensions
Is Data Warehouse Automation a Necessity? Rick van der Lans, R20/Consultancy
It’s 2016 and still ETL programs are being developed manually, data models are still being created by hand, and star schema data marts are still derived from normalized data warehouses manually. Designing and developing BI environments is still a laborious and error prone type of work, and very often, the wheel is invented over and over again. But it shouldn’t be. Manual development is slow, we all know that. Now, the business requirements have changed drastically over the last ten years. One of the key changes is time-to-market; new reports have to be developed more quickly and maintaining existing ones should be simpler. Too often, as a reaction, analysts working at business departments develop their own reports and their own ETL processes, they don’t even call the IT department anymore. Sometimes that’s a good idea, but not always. Organizations have to find ways to improve productivity. One of these alternatives is data warehouse automation. This allows developers and designers to focus more on the business aspects of a BI environment and have to spend less time on repetitive and time-consuming tasks. This session explains how data warehouse
automation can help speed up development.
• Business requirements have changed over time.
• Generating data models for data warehouses and data marts.
• What will data warehouse automation mean for your current BI system?
• How efficient is generated ETL code?
• Pros and cons of data warehouse automation. Integrating Big Data Analytics into a Self-Service BI Environment Mike Ferguson, Managing Director, Intelligent Business Strategies
This session looks at how advanced analytics such as machine learning, graph analysis and text analysis can be integrated into a self-service BI so that business analysts can exploit the power of Big Data analytics platforms such as Hadoop, Spark and Graph databases to add new insights to reports and dashboards. It looks at how self-service BI tools can connect to a logical data warehouse consisting of traditional data warehouses, Big Data and streaming data and how they can invoke advanced analytical models to provide deeper contextual insights.
• The logical data warehouse – new platforms and rich pickings for self-service BI
• Data Science meets self-service BI - new types of analytics available to business analysts
• Machine-learning, text analysis and graph analysis
• Streaming analytics
• What are these kinds of analytics and what can they do?
• Approaches to integrating advanced analytics into self-service BI
• Integrating predictive models with Self-service BI
• Integrating text analytics with self-service BI
• Integrating graph analytics and self-service BI
• Building ‘Situational Awareness’ dashboards using real-time streaming analytics and a self-service BI
Knowing What To Do By Using Data from the Future Håkan Edvinsson, CTO, Informed Decisions
Tomorrow’s outcome is a result from today’s decisions. So why make decisions based on data, which usually reflects the past? Statistical business management has been standard for over fifty years, where top managers rely their decisions on numbers, focusing on past outcomes, performance figures and forecasts. Of, course, we need to learn from history, but we also need to understand what may come. We need data from the future.
Now, in the zettabyte era, we have all the statistics we could ever wish for. But it does not help us understand what decisions we need to make. Furthermore, once we understand what decisions to make, the data won’t tell us what will be the best thing to do. This speech is about how the decision processes need to be modernized and how we can create “data from the future” that helps us to understand what will be the impacts of today’s decisions.
• Get the most from the data analytics but realize the shortcomings in the analytics and the fantastic presentation layers. Wherever you are missing data, which you always will, you need to combine qualified
assumptions with the data analytics in a controlled way.
• Start with the outcomes, and not the data. Clean data, intelligent data analysis tools, and simulation capabilities combined with human expertise, can actually bring data from the future. Trying out various scenarios before trying something in real life saves time and money. Do this by building a decision model based on the outcomes you strive for. It will guide you through possible “what if ’s” and will use the most from your data assets. We have been visualizing and modeling processes, data and software for decades. The turn has now come to model decisions.
• Recognize decision making as a team activity. Generalists usually make better decisions than specialists and teams are more powerful that lone wolfs, even though we tend to admire individuals that are capable of making complex decision by themselves. But, the combination of data analysis tools with the collective intelligence of specialists is even more powerful.
This decision making process has been tested in several Scandinavian organizations and decision model examples from the mobile technology industry, services sector and municipal administration will be shown.
Taking the Internet of Things Beyond Data to Actionable Insights Hylke Peek, Consultant Performance Monitoring, The Backbone and Niels Naglé, Data Solution Consultant/Trainer, Info Support
Enterprises across the globe are looking to IoT-solutions to gain competitive advantage for their products and services. Watching an end-to-end demo is exciting but doesn’t tell you the whole story. More interesting is the journey to implement a real-world smart IoT-solution from concept to product. Within an IoT data flow you can have multiple places where analytics can play an important role to create business value to your solution. You can also have different kinds of analytics in your architecture.
In this session we look at the implementation of a smart presenter where a presenter gets live feedback from the presenter, the audience and other ‘devices’. This – full cloud - prescriptive solution tells you what to do to improve your presentation. We’ll discuss the landscape of IoT & Analytics and our personal lessons learned during this implementation.
• Understand the potential of data and datafication
• Where/How to position Analytics within your (smart) IoT solution
• What are the main challenges of incorporating Analytics into IoT
• How to begin creating your strategyENTERPRISE DATA
CASE STUDIES
Data Governance as a Force MultiplierLt Col Mike Servaes, Data Strategy, British Army
On a personal basis Mike has travelled the circle from Data Governance is a good thing……because it is, through it is not really required and is just an additional cost and delay in the process of using data to a position where Data Governance is an enabler in gaining value from the data an organisation collects etc. This case study will look at the effect of governance for its own sake and then look at how organisations and the British Army in particular are using Data Governance to derive value. In the case of the Army the presentation will look at the differences in approach between and organisation that is seeking to monetise or gain additional profit from its data to an organisation that is seeking to gain addition effect. The Army will seek to gain additional effect from its tax pounds and when operating in an operational context to use the information it gains to multiply its effect on the ground. There will also be a nod to the requirements for all Armed Forces operating in a Joint or multinational environment to combine their data to increase their effectiveness and the Data Governance required for that.• Look at Data Governance Journey• Understand differing approach between
monetisation and Force Multiplication• The Army experience
It’s All Just Data Governance Isn’t It?Garry Manser, Head of Data Governance, Visa Europe
We think of Data Governance as being formulaic, linked to static frameworks and based on well thought out theory. But does that work in the real world. Having worked in a number of organisations Garry has found that whilst the theory works, in practical terms you have to be more fluid. This presentation will look at the differing views of Data Governance he has encountered and the ways he has looked to align with them and still deliver a successful program, it will also look at some of the mistakes that he and others have made and the impact they have had on the projects. In this session Garry will look to show that:
• Data Governance is not a “one size fits all solution”, it has to meet the aims of the organisation
• The ways Data Governance can be delivered are adaptable and fluid
• Real world examples of both good and bad implementations
Information Architecture as a Driver for Enterprise Data Integration at Boehringer Ingelheim PharmaMartin Fleming, Enterprise Architect & Rainer Remenyi, Enterprise Architect, Boehringer Ingelheim Pharma GmbH & Co. KG
Boehringer Ingelheim is a Research driven pharmaceutical company that has a complex value chain reaching from discovery research to market supply. The different parts of this value chain have been supported by business units acting quite independently from each other including the
View full conference programme on irmuk.co.uk/edbi201610
way they were handling their data. The company underwent a transformation towards a more integrated approach, e.g. Research and Development units were combined in an Innovation Unit. This session describes how Information Architecture creates a foundation to succeed on an Enterprise Data level. This session will outline the strategy; lessons learned how these activities are put in place. • How does Information Architecture support and
drive the transformation of the company on an Enterprise Data level?
• What are the achievements?• Where are the pitfalls?
From Data Blind to Data Funded: The IFC World Bank Group Story Gwen Thomas, Corporate Data Advocate Jennifer Trotsko, Head, Data Governance Office, Sana Al-Hajj, Manager, IFC World Bank Group
Every organization has a process for funding technology projects. But what about data work? What about foundational efforts, governance, and tasks that project managers may be blind to? What about data maintenance and improvement activities that don’t map easily to projects? This is the story of IFC (the private sector arm of the World Bank Group), who in 2 ½ years went from “invisible” data needs to a well-funded, interdependent set of projects and work plans. Attendees will learn:• How a small team of individuals were able
to influence the organization’s approach to executing and funding data work
• The carefully aligned strategy they employed, and how it involved Data Management, Data Governance, Business Intelligence, Security, Auditing, IT Governance, and IT Portfolio Management
• 5 funding models, and when each was deployed
How to Survive the CEO’s Trough of Disillusionment with DataRoberto Maranca, Managing Director Enterprise Data, GE Capital
Roberto will discuss how Data Executives can construct a compelling story and influence their peers to advance new innovative business strategies. He will make you understand what the role requires and the critical skills needed to bridge the gap between data, technology and strategy to execute Change. He will cover how you should use communicative skills internally in order to market Data Management to all the firms levels and grab any opportunity to foster adoption. You need to build an enterprise wide vision to establish common goals and cohesion for sustainable and beneficial business transformation.
The Journey to a Data-Driven CultureIan Wallis, Head of Data, Analytics & Insight, Defence Infrastructure Organisation
In September 2014 the Defence Infrastructure Organisation (DIO) embarked on a new strategy, introducing an insourced management team via a strategic business partner consisting of a consortium of three private sector companies. This also heralded the introduction of a new directorate within DIO – Data, Analytics & Insight – to bring data to the forefront of the organisation and change the culture to be data-driven and evidence-based. Data, Analytics & Insight has driven a significant change in less than two years, delivering a data management programme that encompasses data governance (15 Data Owners across DIO), data architecture and modelling, and most recently data quality metrics to drive accountability. MI has been transformed to be
a dashboard-based series of key indicators driving decision-making at senior levels of the organisation, and a BI programme has been initiated bringing data together from across the breadth of the DIO for the first time whilst rolling out BI tools and a data warehouse to several hundred staff. Building on these foundations, analytics and insight are exploiting the data, developing models and geospatial analytics to add value whilst also extending knowledge through research and benchmarking. Data, Analytics & Insight has reached a maturity at which the combination of establishing the strategic pillars and delivering quick wins has begun to reap benefits. Clear changes in behaviour can be seen in DIO as a result and the future influence of the directorate is likely to grow as the outputs add more value. The Quality in Master Data QualityDana Julinschi, Master Data Governance & Projects Manager, Friesland Campina
The end goal of our MDM endeavours is to ensure the quality of our master data is suitable to support the business processes and reporting needs, at the lowest possible cost. But how can we turn data quality into a way of living for the organisation, without making it just another formality? Within Friesland Campina this topic is part of their journey, with its challenges, successes and failures. They have gone a long way with their governance organisation and they intend to go even further. Dana will share with you some of the things they have learned so far, by answering the following questions: • Who needs data quality and why?• To which extent do we measure master data
KPIs and to what purpose?• How do data quality and master data governance
intertwine and support one another?
Progressing an Enterprise Wide Data Accountability Structure From the Design Stage to Operational Effectiveness – Case Study from Yorkshire Building Society Group Ellie Fitzpatrick, Data Governance Manager, Bethany Lancaster, Senior Data Governance Analyst, Yorkshire Building Society Group
Typically there are significant challenges identifying and assigning accountability for data. These include a lack of industry standards and challenges getting buy-in for the concepts and the more complex the organisation, the bigger the challenges are. However an accountability structure must be defined for data governance to become embedded and operationally successful. During this case study session the authors will provide insight into the journey at the Yorkshire Building Society Group, sharing lessons learned and practical advice. The session will cover:• How to approach the design of an accountability
structure for data• Leveraging the development of a Data Dictionary
to embed the accountability structure at YBS• Navigating out of the inevitable troughs that
occur during the implementation journey
From Small Experiments to Viable Data GovernancePetr Podany, Head of Data & Analytics, Sberbank CZ
Interesting things often start small and out-of-sight. This story started out as a small metadata management exercise but it has now evolved into a whole company data governance and knowledge management initiative. Petr will share their story of real people implementing practical, enterprise data
governance in a small European bank, where every (FTE and) penny counts. Petr will share all the important lessons learned and also show you what the result looks like.• How did we make DG visible to everyone?• How did we get people on board?• Data Governance shouldn`t be a big deal
BEST PRACTICE
Data Quality – A Different Perspective Neil Storkey, Independent Consultant Palash Banerjee, Associate Partner, IBM
You want to have Data Quality reporting available across the company but cannot justify the upfront cost and ongoing outlay to your management. Neil and Palash will present the journey from conception to delivery of a ‘pay as you go’ Data Quality Service. A pioneering approach to the delivery of data quality reporting based on Cloud infrastructure outsourced resourcing through a workflow enabled governance process. This session will focus on:• The initial concept• Design• The final product• Challenges faced
Fostering Data Babies - Engaging a Younger Generation of Information ProfessionalsTony Mazzarella, Analytics Solutions Architect & Data Governance Lead, Financial Servicces Industry
Growing up in the digital age may lend to an increased aptitude for understanding data and information management but without the principles, history and guidance from those with decades of experience things can go awry. Due to increased awareness, demand and a global change in climate towards “geeks” (we’re cool now!) Data Babies are coming into the profession through various non-traditional paths with new ideas, misguided ideas and bad habits in tow. In this session, you’ll hear from a know it all Gen Y’er, who realised quickly that he hadn’t even scratched the surface of the history, complexity and savvy that required to succeed in enterprise data. Attendees will come away with ideas in engaging snot-nosed data geeks and gain insight as to where they came from, how their paths are different and how to speak their language.• Understand new paths to the data
profession• Explore generational knowledge gaps• Engaging and fostering young data talent
Data Quality Distilled: An Essential Guide for Data Management Professionals Jon Evans, Information Strategist, EQUILLIAN
Today, more than ever, the quality of data underpinned by a robust approach to Data
View full conference programme on irmuk.co.uk/edbi2016 11
Conference Sessions
Quality Management, is critical to the success of every organisation. Unfortunately, it is a topic that is still impenetrable to many through the use of unfamiliar jargon and too much emphasis on technology.
In this session based on Equillian’s established data quality primer, Jon Evans seeks to redress the balance, by taking the audience on a whirlwind journey from first principles right through to advice on establishing a Data Quality Programme. Along the way, both beginners and those already familiar with the topic will benefit from a business-focused approach, based on industry best practice coupled with many years of experience helping organisations tackle their Data Quality challenges. The session will be structured around 4 key topics:.• Why should I care about data quality?• Monitoring data quality• Improving data quality• Developing a DQ Programme
Become a Data Superhero Rob Zagey, Senior BI Analyst, STANLIB
DATA IS KICK ASS and we all need to become the superhero because it’s changing the rules of work. Companies that are rich in data will be the outperformers. But for companies to be rich in data, employees have to grasp its importance. This BECOME A DATA SUPERHERO session will empower you and your organisation to leverage the power of data into your work and workplace. You will learn:• A very brief history of data• Why is data so important?• Can data change the world?• Working with data - the fundamentals everyone
should know
This talk is for you if:• You’re technical - If this is you then you’ll come
out of the talk and workshop knowing how to market what you do to the business so they’ll jump up like screaming lunatics saying, “yes man, give me all of that and more, and I want it yesterday”
• You’re in the business - If this is you then you’ll come out the talk and workshop knowing that data driven businesses are the best businesses in the world and you’ll want to put data driven at the core of your business strategy.
Ethics in Information Management PracticesKatherine O’Keefe, Data Governance & Privacy Consultant, Castlebridge
Ethics is the new black in Information Management these days, or so it seems. From the European Data Protection Supervisor publishing an Opinion on Big Data Ethics, to countless articles about the call from data scientists for clarity on ethics, there is a growing consensus that “something must be done”. The challenge arises in moving from abstract discussion to practical application.
We need to move beyond talking about Ethics to implementing ethical frameworks in our information management and information governance initiatives. This session describes a soup-to-nuts approach for defining ethical frameworks for information management, setting a model for understanding how ethics affects and is affected by the Business, Information, and Technology management structures we put in place to meet customer expectations of
Information and Process outcomes. A case-based practical focus will ensure knowledge is practical and applicable, not just theoretical. Key takeaways for this session include:• An overview Ethics and their relevance to
Information Management practices• Ethics of Privacy and Human Rights• An overview of practical methods to align ethics
with Information Governance• Risk management, Information management
practices
Turning the Telescope - Humans as Data Systems Mike Culley, Chartered and Occupational Psychologist
This presentation gives a new insight into how we can gain a different and deeper understanding of the dynamics of many human groups – such as teams, organizations and even whole societies – by changing our perspective and viewing them as systems both containing and using information, and affected by the availability, flow, and quality of data within the system.
How is data used as a resource in the real world of human interaction? How do data silos, flows, errors and redundancies cause changes in behaviour and interactions? What could psychology learn from data management, and vice versa? We’ll be looking at these aspects, and more.
The presentation is designed to be engaging, and enjoyable – mixing a little light humour with real thought provoking ideas about both humans and data management in a unique context.
Expert Panel: Building your Career in Data Moderator: Mike Simons, Associate Editor for CIO.co.uk, ComputerworldUK and Techworld, IDG Panellists: Peter Segal, Ogilvie & Associate, Ken Mulkearn, Incomes Data Research
Data specialists have never been in more demand, but are those with real data skills adequately rewarded and are those with real skills under threat from those jumping on the Big Data bandwagon?
This session will look at general trends in business technology, Big Data and regulation and their impact on your career and look at strategies to build your career in data. Panellists include business technology, pay and HR experts and a leading headhunter.
This session will highlight:• Pay and HR trends for business technology and
HR experts• Opportunities and threats to those building a
career in data• Strategies for building your career in data and
business technology
BIG DATA Right Sizing Big DataMichelle Teufel, Strategic Change Leader - Business and Technology Transformation for the Digital Age
Data of all volumes, BIG and SMALL, and, the information it represents is the very life blood of an organisation in today’s digital world. In addition to being generated as a result of our operational activities, our increasing use, restructuring, transformation and analysis of that data is creating
yet more data. This session will discuss:• Implications of this reality in helping business
come to terms with what actions to take and in what order the create a data ecosystem that is sustainable and valuable.
• Practicalities to be considered and thought through
• Opportunities for quick wins to help gain support for investment where needed
Architectures for Big Data AnalyticsMarkus Helfert, Senior Lecturer, Dublin City University
Data is the raw ore whose transformation yields the currency of this capricious information economy. Unlike metals hewn from the earth, new data rushes into the modern world from a swiftly increasing array of sources in a welter of forms from personal devices, cars, buildings, cities and an exponentially increasing array of sources that are becoming smarter with each passing iteration. As raw data resources proliferate around us, information architectures to accommodate its transportation, aggregation and transformation into information products have become acutely important to organizations of all stripes around the world. In this presentation, we will explore the essential characteristics of information architectures to generate decision options from complex, heterogeneous and unstructured data sources, and discuss some examples of high-performance analytic systems. What attendees will learn:• Challenges inherent in big data volume, velocity
and variety• Architectural approaches to decision support for
big data• Information Quality Challenges related to Big
Data• Examples of big data analytics system
implementations
How is Big Data Changing the Paradigm of Sports Valéry Bollier, CEO, OulalaGames Ltd
During the last World Cup, three companies made predictions on the results of the final phase of fifteen matches. They were demonstrating the ability of their advanced technology to predict the outcome of football matches. Microsoft and Baidu correctly predicted all fifteen results while Google made only one mistake... How were they able to make such accurate predictions? They crunched and analysed large numbers of historic results - what we call “big data” - and used that analysis to make their successful predictions. It seems reasonable, therefore, to ask ourselves whether big data is changing the paradigm of the sports industry?
European football teams have started to use statistics much more over the last decade and the methods are becoming more and more sophisticated. The first club in the Premier League to do so were Bolton Wanderers and just a few years later almost every club in the top flight are using statistics to monitor player performance. It therefore seems that big data is genuinely changing sport, but it is also changing the games that are based on sports, for instance fantasy sports. Key learning points:• How Big Data is changing the way we watch
sports and interact with sports clubs• The importance of Big Data for skill games• The role of Big Data in traditional sports betting
vs. fantasy sports betting
View full conference programme on irmuk.co.uk/edbi201612
Panel Discussion: Riding The Elephant: The Governance of Hadoop Environments Moderator: Brian McKenna, Business Applications Editor, Computer Weekly Panellists: Alasdair Anderson, EVP Data Engineering, Nordea Bank, Mike Ferguson, Managing Director, Intelligent Business Strategies, William McKnight, Consultant, McKnight Consulting Group, Luca Olivari, Chief Data Officer, Contactlab
The Hadoop family of open source technologies has been maturing in recent years. It has spawned many and varied instances in companies and organisations, mostly departmental, even siloed in nature, sometimes more central and strategic. Security has been something of a non-issue, and so, too, governance.
• How can Hadoop data pools or lakes be incorporated into well-governed enterprise data systems disciplined by master data management programmes? Should they be?
• Do big data technologies pose problems of a qualitatively different kind to those of more traditional data warehouses, data marts, and relational databases more generally?
• Does the governance of unstructured data repositories, and of the analytics performed using them need, perforce, to be lighter in touch?
• And what of the organisational design problems posed by Hadoop? Does it call into being a chief data officer? Does it entail building a data science team, and, if so, of what kind so as to deliver business value?
This session will address these and other questions, from technical, legal, commercial and organisational politics points of view
DATA INNOVATION
MDM in Financial Institutions - and What’s Next?Lukas Mazanek, Head of Data & Information Competence Center, Raiffeisenbank
With data being the key asset for financial institutions, its quality is of utmost importance. An agile, two-speed (bi-modal) IT approach is becoming quintessential to keep up with an ever-increasing velocity of business, challenging requirements for compliance (e.g. GDPR), fast time to market, and operational excellence. Join this session to learn how a major European bank tackles data quality and MDM, and sees its further operational and analytical use. Building a Data Infrastructure for a Smart City Rutger Rienks, Program Manager, City of Amsterdam
This presentation will be about the struggles they face within the city of Amsterdam in transforming the local government into a data-driven organization in a smart city context. Can they apply change management strategies and what can they learn from epidemiology to upscale abilities? The creation of the data infrastructure as well as the influencing involved to kick-start this development will also be discussed. Following a number of examples that
increased citizens’ wellbeing as well as the local governments’ effectiveness, expectations are high. But how do you keep up with these and how to mobilize the workers in the city to abide advice presented by computational models?
Open Data I Love It! But Not My Data, It’s Special Lisa Allen, National Data Integrity Manager, Environment Agency
The Environment Agency is a public sector organisation. They are part of the Department of the Environment whose approach is to open up all their data for use without charge or restriction. Their data is automatically open, unless there’s a good reason not to share it. The session will take you on our journey from charging for our data to being an open data organisation. In this session Lisa will
• Explain what being an open data organisation means for us
• The cultural shift needed to be open by default
• The amazing uses of our open data
The Data Renaissance: Leading Your Business to the Modern Age Anthony Algmin, Chief Data Officer, Uturn Data Solutions
The Renaissance was a time during the 14th-17th centuries that is considered the link between the Middle Ages and modern history. It was a time of incredible artistic progress, a time when a fundamentally new kind of thinking took hold. We are living in a similar time with respect to data. We have seen tremendous progress in the last decade: with the advent and ubiquitous adoption of handheld computing; a complete upheaval of transportation with car and ride-sharing services and soon, autonomous vehicles; and even a return to space exploration funded by private enterprise.
Though nobody can predict what the future holds, we do know that our companies must do something different to remain relevant. This session will focus less on the specific technologies in focus today, and more about how to create a culture that embraces, and ideally drives, the constant disruptive change of today’s world.
• Why adapting to what is new today is a fool’s errand
• How to take an approach that works far better
• Why although everything is different, nothing has changed — and although history repeats itself, the cycle times are always getting shorter
View full conference programme on irmuk.co.uk/edbi2016 13
Conference Sessions
Testimonials
“As always enjoyable and informative, picked up many ideas to take back.”Alistair Fian, Senior Developer, Standard Life
“Excellent event that had great resonance to my role and have learnt concepts that I can use to drive BI&ED projects. Keynotes were very good.”Neil Lamb, BI Solution Archi-tect, BAE Systems
“My first event. Definitely back next year as it was very good. The quality of information was very high. Good speak-ers delivering good content.”Andrew Davies, Information Architecture manager, BAE Systems Naval Ships
“The conference continues to provide a comfortable and effective platform where we can learn new things, be reminded and refreshed in things we already knew and feel part of a data community which has similar challenges to ourselves.”Andy Moore, Process Specialist, Rolls-Royce
“ED&BI is the most beneficial conference I’ve attended in the past 5 years – specifically in terms of breadth of topics, content and speakers. Excellent organisation throughout.”Michael McMorrow, Principal, MMM Data Perspectives Ltd.
“Enjoyable event with relevant informa-tion helping to keep industry workers up to date.”Luke Paul Buttigieg, Software Developer, MITA
“First time attending – really enjoyed. Will look to come back in the future.”John Daniels, Data Migration Manager, United Utilities
“Good variety on offer and definitely enjoyed the talks and incorporation of real-world corporates and how they are addressing real-issues on the Big Data space.”Victor Ochieng, Data Ware-house Analyst, Plan Interna-tional
PERSPECTIVE SESSIONS
Taming the Data LakeMark Pritchard, Sales Engineering, Denodo
Big Data technologies offer a way of consolidating the continual flow of raw data generated from interactions between the enterprise and the external world, and internally within the enterprise. While consolidation of data into a Data Lake seems a good way of harnessing this stream of data, it poses several challenges that can reduce the effectiveness of turning this raw data into an enterprise usable asset. This session highlights how Data Virtualization is being used to tame the turbulent nature of data lakes, improving enterprise readiness, providing access to enterprise relevant data quickly and cost effectively. This will be illustrated with two case studies of data virtualization deployed in this context. Create BI Success with Effective Dashboards Carl Edwards, Senior BI Consultant, Yellowfin
Dashboards are the No.1 technology for implementing business-driven BI (TDWI). But, up to 80% of BI projects fail (Gartner). The reason? Most dashboards don’t communicate information effectively. Attend this session to discover the top 10 best practices for producing effective dashboards and create BI success.
The 5 Must Do’s for Guaranteed Data Governance SuccessPatrick Dewald, Director & Darius Clayton, Director, Diaku Limited
What’s stopping your data initiatives from succeeding? Stuck in endless data committee meetings or just paralysed by fear of the colossal task ahead? In this session Diaku gives you 5 data initiative hacks to start a collaborative data revolution towards a more data driven organisation today.
Data Lakes and Master Data ManagementMichal Klaus, CEO, Ataccama
Ever expanding data volumes and a growing number of data formats and input streams are just a way of life for most midsize and large organizations. Data Lakes are one of the new concepts that seem to be gaining traction, providing benefits from pure processing power and scalability, excellent price to performance ratio, and unprecedented capacity. This translates to business benefits such as dramatically shortened go-to-market times for new products, an individual approach to customers or micro segments, ability to build customer and risk profiles from relevant data sources, etc. This session will discuss new challenges brought by the Data Lakes and how MDM can help.
Data Governance - Slim and SimpleTomas Barta, Co-founder, SEMANTA
I’ve come to the conclusion that the biggest trap facing DG initiatives is how complex they quickly become. Did your DG initiative get stuck because there were too many processes, policies, procedures or committees and too little progress? Why not take a different direction and start from solid ground with solid results?
I am going to present you with our “think less, do more” concept that can make your Data Governance actionable and work across your whole company or business.
DAMA International and the DAMA Chapters - A PerspectiveSue Geuens & Chris Bradley, DAMA
DAMA International is the globally recognised membership organisation for Data Management professionals. During its almost 30 year life it has grown from the initial 3 chapters banding together to form an international body to an organisation with 50 or more chapters worldwide, a constantly evolving Body of Knowledge and an international recognised certification that is becoming the de-facto standard for organisations to benchmark their employees. DAMA I co-hosts a number of recognised annual conferences and encourages their members to attend as many as possible and to become great speakers and presenters. The DAMAI Chapter Model is a great way for individuals to get that face-to-face networking that is so important in an industry which, while as old as the hills, is still “new”. Whether you are in a country or city where there is a local chapter or somewhere out there in the wilds, there is a membership model for you. And no matter, where in the world you are, you can reach out to either DAMAI or a Chapter and get what you need. Sue is the current DAMA I president as well as past VP Operations and was the driving force for DAMA Southern Africa, President from 2009 and currently Past President. Chris is well-recognised in the industry and has been on the DAMA UK Board for a number of years, becoming Chapter Chair this year. Together they will share their knowledge of and experiences with DAMA – both from the international and chapter side. By the time you leave this perspective you will have learned: • Who is DAMA International
• What we do
• Where we are
• What your benefits will be
• How to get certified
• How to contribute to the professions
View full conference programme on irmuk.co.uk/edbi2016 14
Perspective Sessions
HOW TO BOOK
HOW TO REGISTER
IF YOU CANNOT ATTEND YOU CAN PURCHASE THE CONFERENCE PROCEEDINGS ON A USB STICK FOR £300
HOW TO BOOK
irmuk.co.uk
Registration Fees:Full payment or a purchase order is due prior to the conference. Payment may be made in Sterling (£) or Euros (€).
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4 DayFee: £1,945 + VAT (£389) = £2,334
3 Day Fee: £1,595 + VAT (£319) = £1,914
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The registration fee includes the conference lectures, documentation on USB Stick (no printed version of this is made available at the event), refreshment breaks and lunch on each day of the conference. The cost of hotel accommodation is not included in the conference fee.
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