PARTNER

TECHTALK

IBM

InfoSphere Data Explorer – Jump

Starting Your Big Data Journey with

Big Data Exploration

Luke Palamara Senior Product Manager, InfoSphere Data Explorer

Disruptive forces impact long standing

business models across industries

“Data is the new oil.

Data is just like crude.

It’s valuable, but if unrefined

it cannot really be used.”

– Clive Humby

“We have an economy based on a

resource that is not only renewable, but

self-generating. Running out is not a

problem, drowning in it is.”

– John Naisbitt

Shift of power to the consumer

Pressure to do more with less

Proliferation of big data

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The demand for big data solutions is real

The healthcare industry loses $250 - $300 billion on healthcare

fraud, per year. In the US alone this is a $650 million per day

problem.1

One rogue trader at a leading global financial services firm

created $2 billion worth of losses, almost bankrupting the

company.

5 billion global subscribers in the telco industry are demanding

unique and personalized offerings that match their individual

lifestyles.2

$93 billion in total sales is missed each year because retailers

don’t have the right products in stock to meet customer

demand.

Source: 1.Harvard, Harvard Business Review, April 2010.

2.IBM Institute for Business Value, The Global CFO Study, 2010.

The key is to leverage all the data

© 2013 IBM Corporation

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© 2013 IBM Corporation 5

Where to start?

Five key big data use cases

Enhanced 360o View of the Customer

Security/Intelligence Extension

Data Warehouse Augmentation

Operations Analysis

Big Data

Exploration

Big Data Exploration

Find, visualize, understand all big data to improve decision making

Big Data Exploration

Struggling to manage

and extract value

from the growing 3

V’s of data in the

enterprise; need to

unify information

across federated

sources

Inability to relate ―raw‖

data collected from

system logs, sensors,

clickstreams, etc., with

customer and line-of-

business data managed in

enterprise systems

Risk of exposing

unsecure personally

identifiable information

(PII) and/or privileged

data due to lack of

information awareness

Find, visualize, understand all big data to improve decision making

Unlock the value of information when users need it most

Create unified view

of ALL information

for real-time

monitoring

Identify areas of information

risk & ensure data

compliance

Analyze customer data to

unlock true customer

value

Increase productivity &

leverage past work

increasing speed to

market

Improve customer

service & reduce

call times

InfoSphere

Data Explorer Data access & integration

Index structured & unstructured data—in place

Support existing security

Federate to external sources

Leverage MDM and Governance

Discovery & navigation

Leverage taxonomies and metadata

Clustering & categorization

Contextual intelligence

Easy-to-deploy applications

All at big data scale

Providing unified, real-time access and fusion of big

data unlocks greater insight and ROI

Big Data Exploration Quick time to value for big data

discovery & exploration

• Locate and understand existing

data sources

• Expose data for new uses,

without copying the data to a

central location

• Get up & running quickly;

discover and tag relevant big data

• Develop new insights and

hypotheses

• Connect employees with all of the

data at the point of impact

• Use big data sources in new

information-centric applications

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Leverage the full power of IBM’s Big Data

Platform

© 2013 IBM Corporation 10

Secure access to a broad range of enterprise systems

Integration leverages core components of the platform

IBM’s I&G ensures

veracity

Compelling applications incorporating all data types and sources

CM, RM, DM RDBMS Feeds Web 2.0 Email Web CRM, ERP File Systems

Connector

Framework

Data Explorer App Builder

BigInsights

Inte

gra

tio

n &

Go

vern

an

ce

UI / User

Streams Warehouse Data Explorer

Delivers big data exploration and

indexing capability with secured access

that can scale to petabytes of data

Provides intuitive, secured information

access across 30 different repositories

for 125,000 users worldwide

► Reduced duplicate work

► Improved decision-making

► Connect with experts anywhere

► Increased innovation

Global Consumer

Products Company

Data Explorer’s Role in Big Data Exploration

Requirements

• Explore new data sources for potential

value

• Mine for what is relevant for a business

imperative

• Assess the business value of unstructured

content

• Uncover patterns with visualization and

algorithms

• Prevent exposure of sensitive information

Data Explorer Examples

Fusion of data from BigInsights,

Streams, Warehouse, enterprise

applications, web & more

Connect enterprise data and content in

context

Discover valuable data sources and

connections that will yield insights

Harness real-time updates and many

sources of information

Leverage catalogues (i.e. Business

Glossary) to apply structure to

unstructured content for navigation

Jump-start big data initiatives

Explore and mine big data to find what is

interesting and relevant to the business for

better decision making.

Data Explorer is Search for Big Data.

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Integrated

Rich connector framework

Connect to 1000s of data sources

Direct integration with leading IBM

products and platforms

Accurate

Highest level of search relevancy

Powerful search operators

Customizable relevancy

algorithms

Scalable

Analyze trillions of records

Enterprise-class infrastructure

Secure

Align with governance models

Field-level document security

Leverage existing enterprise

security models

Social

Capture tribal knowledge

Annotate search results

360° Insights

Push relevant information to users

See real-time updates of data

Visualize relationship among

entities of interest

Powerful Search Search within documents

Incremental updates to indices

Term position and frequency

determine relevancy

Text Analytics

Tight integration with Big Insights

Dynamic textual clustering

Combine structured and

unstructured content

Proven

12+ years experience deploying

enterprise class search solutions

for some of the largest customers

on the planet

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Highly relevant, personalized

results

Access across

many sources

Dynamic

categorization

Leveraging

Structured and

unstructured content

Tagging and collaboration

Virtual folders for

organizing content

Refinements based

on structured

information

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Expertise

location

Four value pillars represent ROI potential for big data exploration

Improve

Productivity Reduce Risk & Improve Compliance

Leverage

Existing Assets

Increase Revenue

Eliminate data

silos

Leverage

existing research

and knowledge

Eliminate/retire

unused systems

Extract value

from existing

assets

Reduce training

costs

Improve staff

retention

Improve

collaboration

Capture tribal

knowledge

Eliminate

redundant

projects

Equip sales and

service staff with

current, accurate

info

Increase upsell

and cross-sell

Reduce sales

cycle

Increase

customer lifetime

value

Recommendations

Reduce time to

monitor and

comply

Push relevant

regulatory

updates/alerts

Honor pricing,

NDAs, etc.

Single version

of the truth

Avoid penalties

Getting started with big data … here are the

steps

© 2013 IBM Corporation

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Discover Connect securely to all data sources

Provide unified search and navigation

Surface relationships & themes

Assess Identify the value of the data

Recognize users of the data

Establish context of data usage

Collaborate Augment the data with user knowledge

Create personalized views of the data

Identify ongoing integration points

Leverage Build compelling applications using all of your data

Five key big data use cases

Security/Intelligence Extension

Data Warehouse Augmentation

Operations Analysis

Big Data

Exploration

Enhanced 360o View of the Customer

Enhanced 360o View of the Customer Extend existing customer views (MDM, CRM, etc.) by incorporating additional internal and external information sources

Enhanced 360º View of the Customer: Needs

Requirements

• Create a connected picture of the

customer

• Mine all existing and new sources of

information

• Analyze social media to uncover sentiment

about products

• Add value by optimizing every client

interaction

Data Explorer Examples

360°view of customers, partners,

products, suppliers, etc.

Information from many sources all

in a single view

Content and analytics proactively

pushed based on context

Collaboration capabilities

Application framework for rapid

deployment

Leverage MDM to build line of

business applications

Optimize every customer interaction by knowing everything about them.

A customer is a puzzle made up of many

pieces

Professional Life Employers, professional groups,

certifications …

Legal/Financial Life Property, credit rating, vehicles

Contact Information Name, address, employer, marital…

Business Context Account number, customer type,

purchase history, …

Leisure Hobbies, interests …

Every interaction

requires someone

to piece together

parts of the

puzzle Social Media Social network, affiliations, network …

Information about

your customers is

dispersed, forcing

your employees

to extract it piece-

by-piece

Individual silos can answer typical questions, one-by-one

Wiki

Who is best able to help

this customer? Experts

What is her view of

our company? Social Media

Fulfillment

What issues has this

customer had in the past? Support

Ticketing

Where else has she

worked? External Sources

Who is this customer? CRM

What is available

inventory? Supply Chain

Email

How is her company

using our products? Content

Mgt.

What products has she

purchased? DBMS

… but an enhanced 360º

view provides answers in

one application

Enhanced 360º View answers questions that require multiple systems

Wiki Experts

What should I know before

calling her for renewal? Social Media

What marketing materials

should I send? Support Ticketin

g

What’s going on with

this customer TODAY? External Sources

What products can I upsell

this customer? CRM

How can we increase

engagement with her? Supply Chain

Email

How can we get more

customers like her? Content Mgt.

What impact will inventory

have on her? DBMS

Fusion of data from

multiple systems enables

deeper insights—not just

facts

Fulfillment

List of past purchases by this contact from order

tracking system

Recent conversations from multiple sources: e.g., CRM, e-mail, etc.

Product offers based on past purchases and

conversations

Contact information from

CRM

Consolidated list of products owned based on

account affiliation

MDM ensures consistency and accuracy

Master Data Management drives consistency and accuracy in the 360º view

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Unified View of Party’s Information

CRM

J Robertson

Pittsburgh, PA 15213

35 West 15th

Name:

Address:

Address:

ERP

Janet Robertson

Pittsburgh, PA 15213

35 West 15th St.

Name:

Address:

Address:

Legacy

Jan Robertson

Pittsburgh, PA 15213

36 West 15th St.

Name:

Address:

Address:

SOURCE SYSTEMS

BigInsights Streams Warehouse

Master Data

Management

Janet

35 West 15th St

Pittsburgh

Robertson

PA / 15213

F

48

1/4/64

First:

Last:

Address:

City:

State/Zip:

Gender:

Age:

DOB:

360 View of Party Identity

Unified View of Party’s Information

Gaining a complete view of customers is challenging but IBM

has a portfolio of tools to help

InfoSphere Data Explorer

Find and navigate customer

information regardless of

format or where it is stored

Present a unified view,

combined with analytics

InfoSphere BigInsights

Enterprise-grade Hadoop

Landing area for data

Low-cost storage

Processing power for the most

challenging analytics

InfoSphere Master Data

Management

Ensure consistency and

accuracy of customer and

product data

Uncover relationship links in

customer information

InfoSphere Streams

Continuous analysis of fast-

moving customer data for

immediate insights

PureData for Analytics and

InfoSphere Warehouse

Analysis of operational customer

data in real-time

What is the path to ROI? Sample client progression C

ap

ab

ilit

ies

Bu

sin

ess B

en

efi

ts

Connect to enterprise & web content

Integrate MDM

Create customer/product dynamic pages

Provide consistent view of products & customers to improve ALL customer interaction

Reduce or re-purpose head count through increased productivity

Increase savings by retiring redundant systems or moving to cheaper storage

Integrate collaboration tools

Reveal insights

Build out user preferences

Retire redundant systems

Enable positive customer outcomes

Integrate recommendations

Add additional content sources

Federate analytics

Promote up-selling & cross-selling through dynamic recommendations

Productivity Revenue

Phase I Phase II Phase III

Have you considered the impact on your business of not providing a single point of access for all customer-related business? Lost productivity? Opportunity cost?

Are you able to weigh insights about your customers from social media, surveys, support emails and call records in context with information from transactional systems?

Where to go from here - ask yourself these questions

When someone in your organization wants to view all information about a customer, product or competitor how do they go about it? How many different systems do they need to access?

Are you able to combine your structured & unstructured data together to run analytics & create a more consistent view of your customers?

How would a complete view of the customer enhance your line of business? Are there specific business outcomes you are looking for?

Get started on your big data journey today

Get Educated

– IBM Big Data platform webpage

– IBMBigDataHub.com

– Big Data University

– IBV study on big data

– Books / analyst papers

– IBM Big Data YouTube Channel

Schedule a Big Data

Workshop

– Free of charge

– Best practices

– Industry use cases

– Business uses

– Business value assessment

THINK

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Luke Palamara

lpalamara@us.ibm.com