tdwi chicago presentation: is the logical data warehouse, logical?

© 2015 IBM Corporation

Is the Logical Data Warehouse, logical? Nancy Hensley

Director, IBM Analytics Marketing

March 2015

© 2015 IBM Corporation 2

Agenda

Embrace all data to drive competitive advantage

IT systems evolution

The traditional data warehouse yielding to the logical data warehouse

IBM’s point of view


Data is the new basis of

competitive advantage Front runners will:

Drive business outcomes by applying more sophisticated analytics across

more disparate data sources in more parts of

their organization.

Capture the time value of data by developing “speed of insight” and “speed of

action” as core differentiators.

Change the game in their industry and profession by

infusing analytics into everything.

Our point of view


Enable all analytics

Embrace all data

Run at the speed

of business

1

2

3 Results quickly

& easily digested by anyone

Analytics deployed anywhere

Data analyzed

anywhere

and infused

everywhere

Successful Organizations… The Analytics Culture

Analytics is only as good as the data that fuels it


Disruptions in today’s data centers

Today’s Requirements Disruption to the

Data Center Market Data Points

Users want the ability to build and consume

things on their own – Self-service & Agility Cloud

Spending on Cloud based BD&A solutions will

grow 3x faster than on-premise solutions1

• Increase in social, machine and other new

data types

• Lower cost of data for analytics

• Take advantage of the pace of open

source innovation

Hadoop, Spark

Hadoop, Map-Reduce market expected to hit

$2.2B and CAGR of 58% over next 5 years2

Need for insight and faster time to value Data Appliances

Appliances can provide an impressive 15-

30% TCO reduction for data warehouses3

Faster ability to get to relevant data and

insight Cognitive

50% of consumers will interact with services based on cognitive

computing on a regular basis by 20181

Need for operational analytics at point of

engagement

Low latency analytics on

transactional data

There is increasing pressure to exploit data

for decisions ”in the moment”4

The ability to access all forms of data for

analytics regardless of the data container in

which they reside

Logical data warehouse

By 2017, most business intelligence and

analytics platforms

will natively support multi-structured

data and analysis5

1”IDC FutureScape: Worldwide Big Data and Analytics 2015 Predictions”, IDC, Dec. 2014. 2”10 Hadoop Predictions for 2015”, Computer Business Review, Dec. 2014. 3”The Future of Data Warehouse in an Era of Appliances and Big Data”, Wikibon, Feb. 2013. 4”The Analytic-Transactional Data Platform: Enabling the Real-Time Enterprise”, IDC, Carl W. Olofson, Dec. 2014. 5”Information and Analytics Predictions Through 2020”, Gartner: Douglas Laney, Ehtisham Zaidi, Date: Jan. 2015.


Is it time to invest or pull back?

Front runners reap great rewards

69% of front runners created

a significant positive

impact on business

outcomes using data and

analytics in the past three

years2

60% of front runners created a

significant positive impact

on revenues using data

and analytics in the past

three years2

53% of front runners created a

significant competitive

advantage using data

and analytics2

Analytics pays back $13.01

for every dollar spent1

250% is the ROI of solutions

that incorporate predictive analytics3

1 Analytics Pays Back $13.01 for Every Dollar Spent” Nucleus Research, September 2014 2 Analytics: The speed advantage” IBM Institute of Business Value, 2011 3 The Business Value of Predictive Analytics, IDC, June , 2011


Employees

• Data Warehouses

• Business intelligence

Systems of Insight

Systems of Engagement

• Mobile apps

• Customer management

• Social technologies

• Data analytics

Systems of Record

• Enterprise Resource Planning

• Financial Systems

• Transactional & Operational

Systems of Insight

• Analytic applications (descriptive,

evaluative, predictive, cognitive)

• Data Warehouses


Consumers

Line of business Data Scientists Business Analysts

Partners

Executives

IT Systems have evolved and affect how we think

Digital Devices


Smart products Employees

• Data Warehouses


Systems of Insight


• Mobile apps



• Data analytics

Systems of Record




Systems of Insight



• Data Warehouses


Consumers


Partners

Executives

Let’s look closer at the evolution


Smart products Employees

• Data Warehouses


Systems of Insight


• Mobile apps



• Data analytics

Systems of Record




Systems of Insight



• Data Warehouses


Consumers


Partners

Executives

Let’s look closer at the evolution

Systems of Record

• Transactional &

Operational

• Enterprise Resource

Planning


Systems of Insight

• Data Warehouses


• Analytic applications

(descriptive, evaluative,

predictive, cognitive)

Systems of

Engagement

• Mobile apps



• Data analytics


Systems of Record

The Logical Data Warehouse Emerges

Internal Insight

Reporting

Enterprise

Content

Discovery

Exploration

Decision

Management

Predictive

Analytics

Visualization

Systems of

Engagement

Web or Mobile

Systems of

Engagement

Information Governance

Real-time Analytics

NoSQL Doc

Store

Data Warehouse Deep Analytics,

Modeling

Transactional

Systems

Landing,

Exploration,

Archive

Reporting,

Analytics

Logical Data Warehouse

Transactional

Social

Application

ERP

Financial

Video & Audio

Machine & Sensor

Documents

Third Party

Systems of Insight


IBM’s Point of View

Become an analytics drive organization –

embracing all analytics and all data 1

Recognize the logical data warehouse –

utilize the best data store & platform for the type of analytics required 2

Accelerate and simplify analytics with new technologies 3

fuel decisions with better data & analytics

transform service levels for analytics

redeploy resources to strategic initiatives


But where do I start? Common entry points

Add new data sources,

increase usage or

analytic capability

Accelerate analytic

queries or boost

performance

Exploit technology

innovations to

leverage big data

Add flexibility through deployment model choices

Appliances, Software Solutions, Cloud

IBM has solutions to help with each entry point


Data warehousing

The engine for making data smarter, faster

• Data warehouse appliances to

accelerate analytic performance and

increase data & analytic capacity

• Latest in-memory, columnar

technology to boost performance and

lower cost

• Support for new data types to drive

insight and enable exploration

• Cloud services to speed deployment,

and increase agility for your business

Benefits

• Analytics delivered with speed and

simplicity

• Integrated logical data warehouse

to exploit all data assets

• Flexible architecture deployment

options

Key Features


IBM can help you navigate a path beyond the barriers—to better,

faster outcomes

• Diagnose the right architecture for

your needs

• Maximize the value of your existing

investment

• Reduce the cost of implementation

• Get you to your business objectives

faster

1. Leverage experience with

multiple technologies

2. Compare performance

profiles

3. Optimize the deployment mix

4. Apply the right technologies to

accelerate innovation

Our Objectives Our Approach

Leverage technology innovation

for business value

tdwi chicago presentation: is the logical data warehouse, logical?

Technology

big data

structured data

relevant data

forms of data

data run

data container

ibm corporation3 data

traditional data warehouse