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Mission
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FEBRUARY: Analytics
March: OPERATIONAL INTELLIGENCE
April: INTELLIGENCE
May: INTEGRATION
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Analytics
Hindsight and Insight are fairly common
© C
rist
ian
Farc
as |
Dre
amst
ime.
com
PREDICTIVE CAN BE ELUSIVE
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Analyst: Mike Ferguson
Mike Ferguson is Managing Director of Intelligent Business Strategies Limited. As an independent analyst and consultant, he specializes in business intelligence, data management and enterprise business integration. With more than 30 years of IT experience, Mike has consulted for dozens of companies, spoken at events all over the world and written numerous articles. Formerly he was a principal and co-founder of Codd and Date Europe Limited – the inventors of the Relational Model, a Chief Architect at Teradata on the Teradata DBMS and European Managing Director of DataBase Associates where he was a partner with Colin White.
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! Alteryx provides an enterprise-class analytics platform which enables users to combine Big Data with information assets across the organization
! Analysts can perform predictive and spatial analytics, as well as produce sharable apps
! Alteryx’s Strategic Analytics Software is a desktop-to-cloud solution that combines business data, industry content and spatial processing
Alteryx
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Matt Madden
Matt Madden is Senior Product Marketing Manager at Alteryx. He has over 13 years of experience helping organizations realize the power and benefits of analytics in the roles of Sales and Marketing.
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
The New Normal: Predictive Power on the Front Lines
Matt Madden- Sr. Product Marketing Manager
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
• New sources creating huge volumes of “Big Data” • Social Media • Sensors • Radio Frequency ID (RFID) • Log files
• More Data= More Questions= More Decisions
• Predictive analytics provides tremendous potential for high-value analysis & decisions
• Customer Analytics • Marketing Optimization • Market Basket Analysis • Inventory Analysis • Reducing Churn
Decisions start with data
Predictive
Value
Big Data
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
• Traditional Business Intelligence (BI) platforms are backward-looking • Predictive Analytics represents the highest value • Historically, Predictive Analytics have also been the most complex to
implement
Predictive Analytics: A Competitive Imperative
Reporting
Analysis
Monitoring
Prediction
Reporting- What happened? • Query, reporting tools
Analysis- Why did it happen? • OLAP & visualization tools
Monitoring- What’s happening now? • Dashboard, scorecards
Prediction- What might happen? • Predictive analytics
*Source: The Data Warehousing Institute (TDWI) www.tdwi.org
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© 2012 Alteryx, Inc.
• Time-consuming • Requires specialized expertise
The “Old Way” Doesn’t Work Any More
• Expensive • Hard to rapidly iterate
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
• Faster time from question to insight • No specialized skills required
Alteryx Strategic Analytics: A New Approach
• Lower cost • Iteration-friendly
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
Structured | Semi-structured | Unstructured
Integration
Local & Productivity
Alteryx Big Data Architecture – App Design
Inter Source Data Integration
Personal ETL access &
integrate any data
Agile Database large scale, rapid data processing
Data Quality keep your data
clean and credible
Data Management define and map
relationships between data
Analytics Predictive
Drive foresight with R based tools
Statistical Understand and
build models
Spatial Deep understanding of location intelligence
In DB
Analytics
Ingest
Output &
U
pload
Data Warehouse NoSQL Hadoop Big Data
Discovery
Analytics Consumption
Analytic Apps 3rd Party Multiple Format Output
IT / DW Team
(Coming soon)
Publish
Output
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Alteryx blue and tints for headings and main graphics
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Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Alteryx Analytic Workflow – Step 1
Un-Structured Content
App &
Data
All Relevant Data
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Alteryx Analytic Workflow – Step 1
Integrate any data source
Integrate
Un-Structured Content
App &
Data
All Relevant Data
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Alteryx Analytic Workflow – Step 1
Integrate any data source
Integrate
Un-Structured Content
App &
Data
All Relevant Data
Enrich
Packaged Market & Customer Data
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Alteryx Analytic Workflow – Step 1
Integrate any data source
Integrate
Un-Structured Content Rapid design of
predictive analytics
Analyze
App &
Data
All Relevant Data
Enrich
Packaged Market & Customer Data
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Alteryx Analytic Workflow – Step 1
Integrate any data source
Integrate
Un-Structured Content Rapid design of
predictive analytics
Analyze
App &
Data
All Relevant Data
Enrich
Packaged Market & Customer Data
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Create & Share Analytic Apps in Cloud – Step 2
Assemble App
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
Create & Share Analytic Apps in Cloud – Step 2
Assemble App
Private or Public Cloud
Publish
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Create & Share Analytic Apps in Cloud – Step 2
Assemble App
Private or Public Cloud
Publish
Run
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Alteryx blue and tints for headings and main graphics
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Accent colors (use sparingly)
© 2012 Alteryx, Inc.
• Emerging data sources • High volume • High velocity • High variability
• New data platforms • Hadoop • NoSQL
• Alteryx advantage • Easily integrate non-traditional
data • Leverage technology and cost
advantages of next-gen platforms
Integrate “Three-V” Data
Un-Structured Content
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
Harness third-party data sources to provide data on: • Consumers
• Age, income, education, etc.
• Locations • i.e. Local business and
residential spending projections
• Competitors • Employees, revenue,
locations, etc.
• Drive times • Traffic patterns, typical
weather, road types, etc.
Include Third-Party Data for a Complete Picture
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
• Take the value of Predictive Analytics beyond the “Ivory Tower”
• Empower front-line employees • Clerks, customer service
agents, field service personnel
• Harness the power of the R Analytical language
• Over 20 Prepackaged analytic techniques
• No coding required • Drag-and-drop • Tightly integrated
Move Predictive Analytics to the Front Lines
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Key Requirements: • Unify customer data
across multiple sources • Improve direct mail
campaign execution and results
• Maximize revenue generation from catalogue business
• Enhance ROI from mailings
Southern States Cooperative Continues Success With Increased Campaign Response and Revenue
“My number one responsibility is to make sure we understand our customers’ needs and wants, I use Alteryx every single day to do just that ” Greg Bucko, Manager of Customer Insights.
• Customer focused analytics improve response rates by 63% • More targeted mailings improving gross margin for each campaign • Extending insights to full range of customer channels including retail
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Demonstration Richard Snow
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Alteryx blue and tints for headings and main graphics
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© 2012 Alteryx, Inc.
• Organizations must adapt: • From backward-looking to
forward-looking • Beyond traditional data sources • To deliver the value of
Predictive Analytics to the front line
Conclusion
“My number one responsibility is to make sure we understand our customers’ needs and wants, I use Alteryx every single day to do just that” Greg Bucko, Manager of Customer Insights.
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
• Organizations must adapt: • From backward-looking to
forward-looking • Beyond traditional data sources • To deliver the value of
Predictive Analytics to the front line
• Alteryx’s unique approach delivers:
• Far broader accessibility for Predictive Analytics
• Much lower cost and complexity
• Deeper insight into data (Social Media & Big Data, Third-party Data, Traditional sources)
Conclusion
“My number one responsibility is to make sure we understand our customers’ needs and wants, I use Alteryx every single day to do just that” Greg Bucko, Manager of Customer Insights.
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
Contact Info
www.alteryx.com
Learn More or Get the 30-Day Trial:
gallery.alteryx.com
Visit the Analytics Gallery:
@alteryx
Contact us: 1-888-836-4274 www.alteryx.com/contact-alteryx
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Alteryx blue and tints for headings and main graphics
Secondary palette: For support in charts, graphics, and callouts
Accent colors (use sparingly)
© 2012 Alteryx, Inc.
“Overall the best single company sponsored conference I've ever attended.” ─Antoinette Bowen, Sr. Marketing Manager, AT&T Mobility
Inspire 2013
Sheraton Phoenix Downtown Hotel March 5-7, 2013
Learn More! www.alteryx.com/inspire
Follow Us on Twitter! @alteryx #Inspire13
Seize the Power of Strategic Analytics
Alteryx In The Briefing Room
Mike Ferguson Managing Director Intelligent Business Strategies February 2013 www.intelligentbusiness.biz Twitter: @mikeferguson1
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Operational data
web
P o r t a l
BI Tools
Platform Dat
a In
tegr
atio
n / D
Q
Traditional Data Warehousing and Business Intelligence
Reports & analytics
Data warehouse & data marts
DW
Data Warehousing
What is Data Warehousing? Data warehousing is the process of building an analytical system by cleaning and integrating data from multiple data sources The analytical system can consist of 1 or more databases
Business Intelligence
What is Business Intelligence? Business Intelligence is actionable business insight that is produced by querying and analysing data in a data warehouse or a data mart using BI tools A typical organisation has information producers and information consumers.
35
What Is Self Service BI?
“ The creation of a BI environment whereby business users can create and access BI reports, queries, and analytics without the need for IT involvement”
§ Business users need to be able to: • Be more self-sufficient • Collaborate with others to share insights and make decisions • Access personalised business insight
§ Self-service BI options • Data discovery and visualisation tools • Analytical workflow and visualisation tools
§ Self-service BI is NOT about self-service data warehousing • Data governance and common data definitions are critical to
maximising the use of trusted data and facilitating common understanding
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Self-Service BI Data Discovery and Visualisation Tools Allow Users to Quickly Produce Insight – e.g. Insurance
In-memory data Data
visualisation server with in-memory columnar storage
Data discovery and
visualisation tool
DW Underwriting system
Re-insurance data
Ultimates data
Predictive model
e.g. Calculate Net Premiums and Claims even when re-insurance data is not in the DW
community
Consume / Enhance / Re-publish / Act
Publish / Share
insights
37
Self-Service Analytical Workflow Development & Visualisation Tools Allow Users to Quickly Produce Insight – e.g. Insurance
Workflow execution Analytical Workflow Execution
Server
Analytical workflow development and visualisation tool
DW Underwriting system
Re-insurance data
Ultimates data
Predictive model
e.g. Calculate Net Premiums and Claims even when re-insurance data is not in the DW
community
Publish / Share
insights Consume / Enhance / Re-publish / Act
38
Predictive Analytics Are Now Becoming Available In Self-Service BI Tools – But Do Users Know How to Use Them
Data Discovery & Visualisation OR
Analytical workflow server
Business Analyst
DW Underwriting system
Re-insurance data
Ultimates data
Predictive model
Predictive models
community
Publish / Share
insights Consume / Enhance / Re-publish / Act
The challenge is making it easy for non-statistically
trained business analysts to select the right algorithms for the business questions they are trying to answer
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Impact of Self-Service BI/Analytical Tools on Data Management
§ Business users needing data from multiple sources are using front end tools for data integration rather than for data analysis and visualisation
§ Potentially inconsistent data definitions and calculations for the same data created by every user doing their own data integration
§ Potentially a major increase in the proliferation of overlapping data sets created by self-service BI business users not connecting to data via a BI platform semantic layer
§ Potential for multiple versions of unmanaged data scattered throughout the enterprise • Potential for multiple versions of reference data
§ Potential for inconsistent data everywhere and not just created by Excel users
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Self-Service BI
Data Discovery & Visualisation OR
Analytical workflow server
Business Analyst
Data Virtualization
personal & office
data Predictive models
community
Publish / Share Consume / Enhance / Re-publish
Transaction systems
Data Management
DW
Simplifying And Governing Data Access to Improve Self-Service BI – One Approach is Via Data Virtualisation
41
Governing Information Distribution Is Also Important - Information Producers and Information Consumers
Information Producers Information Consumers
Executives, Managers, Frontline workers, Customers, Partners, Suppliers
Business & Financial Analysts, IT Developers, Some Managers
Information Distribution
Govern distribution
Govern who can produce, what data they can access and how they name data
Govern what they can access and what devices they can use Business
glossary
Business glossary
42
Sales
Product line n
Product line 4
Product line 3
Product line 2
Product/service line 1
Marketing
Service
Credit Verification
HR
Finance
Planning
Procurement
Sup
ply
Cha
in
Sup
plie
rs
Front Office BackOffice
Operations
Cus
tom
ers
New Data Sources Have Emerged Inside And Outside The Enterprise That Business Now Wants To Analyse
E.g. RFID tag
sensor networks
weather data Data volume Data variety Number of sources
Data volume Data variety
43
Big Data Has Taken Us Beyond The Traditional Data Warehouse – New Big Data Analytical Workloads
1. Complex analysis of structured data
2. Analysis of data in motion
3. Exploratory analysis of un-modeled multi-structured data
4. Graph analytics
5. Accelerating ETL and analytical processing of un-modeled data to enrich data in a data warehouse or analytical appliance
6. The storage and re-processing of archived data
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The Changing Landscape – We Now Have Different Platforms Optimised For Different Analytical Workloads
Streaming data
Hadoop data store
Data Warehouse RDBMS
NoSQL DBMS
EDW
DW & marts
NoSQL DB e.g. graph DB
Advanced Analytic (multi-structured data)
mart DW
Appliance
Advanced Analytics (structured data)
Analytical RDBMS
Big Data workloads result in multiple platforms now being needed for analytical processing
45
Hadoop ‘Sandboxes’ Are Common for Data Scientist Led Investigative Analysis of Multi-structured Data
Web logs
ETL MapReduce Applications (batch analysis)
new insights
sandbox sandbox Un-modelled data
Seismic data
sensor data
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ETL Acceleration Is Also A Popular Big Data Use Case For Bringing Additional Insights Into Data Warehouses
Cloud Data
HDFS
Extract
DW D I Map/ Reduce
analytical applications
Transform
e.g. PIG, JAQL
Cloud Data e.g. Deriving insight from huge volumes of social web content on sites like Twitter, Facebook. Digg, MySpace, TripAdvisor, Linkedin….for sentiment analytics
Hundreds of terabytes up to petabytes
relevant insight
Operational systems
47
This Requires Parsing & Extraction From Multi-Structured Data While Integrating Data In A Big Data Environment
E-mail (semi-structured)
Text (unstructured)
Extract Parse Transform Load …
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Data Deluge – Need To Accelerate And Automate Data Filtering To Consume Data That Is Arriving Faster Than We Can Consume It
F D I A L T T A E R
Enterprise
Enterprise systems
49
Data Management Tools Are Being Extended To Embrace And Exploit MPP Hadoop Clusters AND Embed Analytics
Parse & Prepare Data in Hadoop (MapReduce)
Load Data into Hadoop
Transform & Cleanse Data in Hadoop (MapReduce)
Extract Data from Hadoop
Discover data in Hadoop
Invoke Custom Analytics on Hadoop
Data management
tools
Approaches: • Custom code • Data Management tools suites • Self-service analytical workflow development tools???
Trends: Expect MUCH more from data management tool vendors including generation of MapReduce code to clean and transform data
50
New Analytical Platforms Breed New Requirements – Cross Silo Analytics for Harder Business Questions
EDW
DW & marts
NoSQL DB e.g. graph DB
mart DW
Appliance
Advanced Analytics (structured data)
Analyse?
Advanced Analytics (multi-structured data)
Streaming data
RT Analytics
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Cross Silo Analytics Option - Multi-Platform Analytical Workflows Need Analytics Embedded in ETL Processing
• Support parsing and extract of data from multi-structured data sources • Help automate analysis and consumption of data • Move the data to the best platform to do the analytics • Support analytical processing across multiple analytical platforms
Extract Parse Clean Transform Analyse Load Insights
Step 1
NoSQL DB e.g. graph DB EDW
Step 3 Step 2
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Discussion Points § Competitive positioning
• Where does Alteryx fit in the analytical competitive landscape?
§ Product positioning • Is Alteryx for Data Warehousing, Self-service BI or both?
§ Data Governance • How does Alteryx facilitate support for data consistency and reuse
§ Analytical workloads • What kinds of analytical workload is Alteryx providing solutions for? • Big Data – How does Alteryx work with Big Data and NoSQL Platforms?
§ Performance • How does Alteryx scale to handle concurrent users analysing and
consuming business insights • How does Alteryx exploit underlying analytical platforms to get
performance with high volume multi-structured data?
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Upcoming Topics
This month: Analytics March: Operational Intelligence
April: Intelligence
May: Integration www.insideanalysis.com
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