Business Agility Must Be Based on a New Flexible and Agile Data Approach

© 2015 Denodo

Craig LeClaireVP, Principal Analyst

Megan BurnsVP, Principal Analyst

Cory MunchbachAnalyst

Holger Kisker, Ph.D.VP and Research Director

Session 1CIO’s Must Enable Business Agility via Modern Data Management in the Age of the Customer

Session 2 Understanding the Customer Experience Ecosystem to Succeed in the Age of the Customer

Session 3 Build a Contextual Marketing Engine and Fuel it with Data

Session 4 Business Agility Must Be Based on a New Flexible and Agile Data Approach

Data Virtualization for Business Intelligence andBusiness Agility in the Age of the Customer

Four sessions providing insights and best practices for the Age of the Customer

WEBINAR SERIES featuring FORRESTER RESEARCH

© 2015 Denodo

Data Virtualization for Business Intelligence and Business Agility in the Age of the Customer

Suresh Chandrasekaran

Senior VP, Denodo

© 2015 Denodo

Business Agility Must Be Based on a New Flexible and Agile Data Approach

Holger Kisker, Ph.D.VP and Research Director

SESSION 4

Making Leaders Successful

Every Day

Business Agility Must Be Based

on a New Flexible and Agile Data

Approach

Holger Kisker, Ph.D.

Vice President & Research Director

Data initiatives are the most important tech investments

Source: Forrsights Software Survey, Q4 2013

Base: 2,074 technology executives and technology decision makers

57% of decision

makers rank data

projects the most

important

investment in

their company

7%

16%

15%

18%

20%

24%

5%

12%

18%

17%

16%

33%

Social related projects

Mobile related projects

Cloud related projects

Systems of engagementapplications

Systems of recordapplications

Data related projects

2nd Priority

Top Priority

Please rank the following technologies according to their

importance and investment within your firm?

© 2013 Forrester Research, Inc. Reproduction Prohibited 7

The main driver is to better decisionsWhat are the most important goals/drivers your organization considers when planning or

orchestrating your business intelligence strategy?

10%

21%

27%

28%

29%

37%

42%

43%

53%

Achieve better business transparency

Develop better products and services

Improve business planning

Gain competitive advantage

Ensure compliance and reduce risks

Improve data quality and consistency

Improve customer interaction andsatisfaction

Monitor, improve, and optimize processperformance

Make better informed businessdecisions

Base: 249 North American business decision-makers

Respondents answering “don’t know” are not shown

Source: Global Data and Analytics Survey, 2014

Business

growth

drivers

Technical

& control

drivers

Turn Data Into Business Insights

More Deeper For Everyone

Deeper Insights

More Data

For Everyone

© 2014 Forrester Research, Inc. Reproduction Prohibited

Culture• Data treated as

an asset

• Data-driven

• Data shared

across silos

Capabilities• Advanced data

management,

delivery and

analysis

Competency• Technology skills

• Analytical skills

• New approach to

data governance

• Agile processes

Success

Ingredients To A New Flexible And Agile Data Approach



an asset

• Data-driven

• Data shared

across silos



• New approach to

data governance

• Agile processes


management,

delivery and

analysis Success



Choose The Appropriate Data Management Technology

Hig

hly

to

po

lystr

uctu

red

Batch to real time

Velocity

Vari

ety

Scalable NoSQL

In-memory

Streaming

Standard SQL

appplianceStructured

historical data

Int./ext.

polystructured

data

In-time

dynamic data

Real-time data

in motion


Not all data needs to fly First ClassFront

Rear


Data

Science

Workbench

HadoopStreaming

SQL

Datawarehouse

Application

In-Memory

Datawarehouse

Any Data

Sources

A new approach to architecture –hub-and-spoke (example)

Advanced data analytics for

deeper Insights

Advanced data management

technologies to use more data

Advanced data delivery technologies

to leverage & share insights


Data About The Future Is The Most Valuable!

10%

14%

13%

15%

14%

18%

18%

23%

18%

21%

28%

29%

37%

31%

27%

28%

31%

5%

7%

8%

7%

10%

8%

12%

11%

17%

15%

22%

22%

26%

36%

41%

44%

53%

Unstructured external data

Social network data

Consumer mobile device data

Weblog data from publically facing sites

Sensor data other than mobile devices

Video, imagery & audio

Partner data

Third party data sets

Scientific data

Log data from corporate systems

Product data

Unstructured internal data

Home-grown data stored in spreadsheets or other…

Transactional data from corporate custom build apps

Customer data

Transactional data from corporate packaged apps

Planning, budgeting, forecasting data

4 5. very important

Base: 634 Business Intelligence users and planners

“How important are the following data types to your firm's overall business strategy?”

Answers 4 and 5 on a scale where 1- not at all important and 5 – very important

Source: Forrsights BI/Big Data Survey, Q3 2012

Data value

$$


Traditional Reporting

Predictive Analytics

You know nothing about your customer

Deeper Customer Insights With Advanced Analytics

Why did he buy our product?

What is he going to need next?When will he need support?

Where is he right now?

Advanced data analytics for

deeper Insights

Advanced data management

technologies to use more data

Advanced data delivery technologies

to leverage & share insights


Visual display and self-service are key

Image source & copyright: http://www.cloudred.com/labprojects/nyctrees/

Image source & copyright: Microsoft



an asset

• Data-driven

• Data shared

across silos


management,

delivery and

analysis



• New approach to

data governance

• Agile processes

Success



New hub-and-spoke architecture

Data

Science

Workbench

HadoopStreaming

SQL

Datawarehouse

Application

In-Memory

Datawarehouse

Any Data

Sources


How Much Hadoop Skills Do You Need?Very few specific skills:

Using „enterprise-ready“

Hadoop solutions, (e.g.

MapR, Cloudera,

Hortenworks)

Some specific skills:

Leverage OpenSource

Ecosystem (e.g. Pig,

Hive, HBase)

Native Hadoop

integration: Java coding

in distributed file system

with map-reduce


› Advanced analytics apply

data models based on

mathematic-statistical

methodologies & algorithms

• What is the right

algorithm?

• Adjust the model to

reflect business reality

Data Scientist: Sexiest Job of the 21st Century

› Vendors start to close the

skills gap with pre-

packaged solutions and

data services

› A team-based approach is

essential: tech management

& data scientist & business

& other experts

Source: http://www.practicaldb.com/demos/

Build

Integrate

UseShare

Self-Service

Skills &

Processes



an asset

• Data-driven

• Data shared

across silos


management,

delivery and

analysis



• New approach to

data governance

• Agile processes

Success



Business outcome

Data sources

Deeper insights

More data

For everyone

What business value

do we want?

Who needs what

insights for this?

What analysis tools

do we need?

How can we

manage all the data

needed?

What data

do we have?

How can

we process that

data?

What can

we learn from this

data?

How

do we deliver those

insights?

Bo

tto

m-u

p te

chno

logy-d

riven T

op

-dow

n b

usin

ess-d

rive

n

What business value

can we create?

What data sources

do we need?

There’s no single right way to plan

Data delivers benefits on different levels

Strategic Benefits (e.g. increased asset value on balance sheet, reduced risk

exposure, improved performance, better planning)

LoB Benefits (e.g. downtime, operational cost, asset utilization, improved

quality, production performance)

User Benefits (e.g. decision support, reduced search time,

satisfaction, self-service, mobile support)

IT Benefits (e.g. data quality, data

utilization, improved models, real-time, improved SLAs)

„Data Will Become

An Asset On The

Balance Sheet“


Everybody can benefit from big data

Base: 1,077 North American and European

Software decision-makers who are using or

Planning to use big data (20+ employees)

“What groups or departments are currently using big data/planning to use big data in

2014?”

Source: Forrester’s Forrsights Software Survey, Q4 2013

Operations

38%

(e.g., supply-demand)

Marketing

34%

(e.g., campaigns)

IT analytics

58%

(e.g., network secure)

Finance

31%

(e.g., risk exposure)

Sales

36%

(e.g., cross-/upsell)

Research

32%

(e.g., simulation)

Customer service

31%

(e.g., segmentation)

Manufacturing

20%

(e.g., process opt.)

GRC

14%

(e.g., auditing)

Product

development28%(e.

g., social feedback)

Logistic and distr.

27%

(e.g., route opt.)

Human resources

19%

(e.g., head hunting)

Procurement

17%

(e.g., best buy)

Supply chain

23%

(e.g., sourcing)

Other

3%

Don’t know

1%

Hadoop

Reporting

Process

Optimization

Data

Management

Data

Processing

Information

Usage

Data

Sources

EDW

Advanced

Analytics

Decision

Support

Engagement

Systems of

Customer

Engagement

In-Memory Streaming

Record

Systems of

Economy

Data


Don’t end up in a (big) data zoo!

Image source & copyright: Teradata

Hadoop

Reporting

Process

Optimization

Data

Management

Data

Processing

Information

Usage

Data

Sources

EDW

Advanced

Analytics

Decision

Support

Engagement

Systems of

Customer

Engagement

In-Memory Streaming

Record

Systems of

Economy

Data

Hadoop

Reporting

Process

Optimization

Data

Management

Data

Processing

Information

Usage

Data

Sources

EDW

Advanced

Analytics

Decision

Support

Engagement

Systems of

Customer

Engagement

In-Memory Streaming

Record

Systems of

Economy

Data

Hadoop EDW Streaming

Engagement

Systems of

Record

Systems ofReporting Advanced

Analytics

Customer

Engagement Economy

DataDecision

Support

Process

Optimization

In-Memory

Data

Management

Data

Processing

Information

Usage

Data

Sources

Data

Sources

Data Virtualization

Data Virtualization

Discovery

Access

Manage

Monitor

Performance

Data

Sources

Data Virtualization

Manage

Unified Data

Governance

• Security

• Privacy

• Quality

• Standards

• Life Cycle

Access

Unified Data

Access to any

• Source

• Application

• Insight

• Employee

• Customer

• Business

Partner

Monitor

Unified Data

Monitoring

• BI on BI

• Compliance

• Health

• Business

Usage

Discovery

Finding the

nuggets

• Sources

• Pattern

• Insights

• Use Cases

• Business

Value

Performance

Optimized Data

Performance

• Workload

Optimization

• Cost

• Availability

• Usability

• Business

Managing the Complexity Of A Modern Data Architecture

Image source: Big Data World Congress (http://bigdatacongress.com/) and c1.staticflickr.com

((//c1.staticflickr.com/1/40/123900378_e668dd966e.jpg)

There is no single ‘best’ data Use Case; start your own road map.

There is no single ‘best’ data technology; see what fits your needs.

Don‘t create data silos; think strategically and put in place a flexible platform & data virtualization

Tech management recommendations

Thank you

Holger Kisker

[email protected]

@hkisker

+49 69 959 29862

© 2015 Denodo

CDO / CIO new calling - Turn MORE data into DEEPER business insights for EVERYONE

Requires new capability, competency and culture of data as an asset

Capabilities at 3 levels of data, analytics, delivery of insights requires variety of best of breed tools

Beware of increased complexities , solution silos, replicated data, Big Data Zoo!

Agile data architecture across layers -data source, management, processing, delivery – to abstract, hide complexity, deliver info faster

Forrester Take Aways Denodo Enablers

Fast data access; Information-as-a-service; Agile integration

Organize canonical business entities used across dimensions

Single View of Customer; Data distribution across channels

Structured & unstructured; Internal & external; Real-time; Self-Service; Less replicated; Virtual

Unified data abstraction layer democratizes access to single source of truth across and beyond organization boundaries

Agile Data Architecture – How Denodo drives it

© 2015 Denodo

Access any source

Make them look homogeneous

Pre-integrated graph of information for users

Build very rapidly

Data services feed many applications & users

ROI?

“..saved 1000s of development hours”

“.. exceeded breakeven expectations – smash through

it!”

“.. tackled business value for more leverage, not IT cost”

Agile Data Architecture – Capital Markets Firm

© 2015 Denodo

Agile Data Architecture – Technology Firm

BI 2.0: Best of breed Complexity! Tamed by Data Virtualization

© 2015 Denodo

Data Virtualization - Two Approaches to Adopt

Solve one/more projects

Prove value

Expand to other use

cases

Reusability and

scalability

Expand enterprise-

wide

Enterprise strategic

vision

Design for scale and support

Systemic data

services

High value use cases

first

Multiple usage

patterns

Tactical

Approach

Enterprise-wide

Approach

People Process Technology

Hybrid

Approach

Possible

© 2015 Denodo

Q&A

© 2015 Denodo

Thank you!

Data Virtualization for Business Intelligence andBusiness Agility in the Age of the Customer

Four sessions providing insights and best practices for the Age of the Customer

WEBINAR SERIES featuring FORRESTER RESEARCH

Date post:	15-Apr-2017
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