PARTNER TECHTALK IBM – Jump

InfoSphere Data Explorer – Jump
Starting Your Big Data Journey with
Big Data Exploration
Luke Palamara
Senior Product Manager, InfoSphere Data Explorer
IBM PARTNER
TECHTALK
Disruptive forces impact long standing
business models across industries
Pressure to do more
with less
Shift of power to the
consumer
“Data is the new oil.
Data is just like crude.
It’s valuable, but if unrefined
it cannot really be used.”
– Clive Humby
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Proliferation of big
data
“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
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.
$93 billion in total sales is missed each year because retailers
don’t have the right products in stock to meet customer
demand.
5 billion global subscribers in the telco industry are demanding
unique and personalized offerings that match their individual
lifestyles.2
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
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© 2013 IBM Corporation
Where to start?
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© 2013 IBM Corporation
Five key big data use cases
Big Data
Exploration
Enhanced 360o View
of the Customer
Security/Intelligence
Extension
Big Data Exploration
Operations
Analysis
Find, visualize,
understand all big data to
improve decision making
Data Warehouse
Augmentation
Big Data Exploration
Find, visualize, understand all big data
to improve decision making
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-ofbusiness data managed in
enterprise systems
Risk of exposing
unsecure personally
identifiable information
(PII) and/or privileged
data due to lack of
information awareness
Unlock the value of information when users need it most
InfoSphere
Data Explorer
Data access & integration
Index structured & unstructured
data—in place
Support existing security
Federate to external sources
Leverage MDM and Governance
Improve customer
service & reduce
call times
Increase productivity &
leverage past work
increasing speed to
market
Providing unified, real-time
access and fusion of big
data unlocks greater
insight and ROI
Discovery & navigation
Leverage taxonomies and metadata
Clustering & categorization
Contextual intelligence
Easy-to-deploy applications
All at big data scale
Create unified view
of ALL information
for real-time
monitoring
Analyze customer data to Identify areas of information
risk & ensure data
unlock true customer
compliance
value
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
IBM’s I&G ensures
veracity
Data Explorer App Builder
Streams
BigInsights
Data Explorer
Warehouse
Integration leverages
core components of
the platform
Secure access to a
broad range of
enterprise systems
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Connector
Framework
CM, RM, DM
RDBMS
Feeds Web 2.0
Email
Web CRM, ERP File Systems
Integration & Governance
UI / User
Compelling applications
incorporating all data types
and sources
© 2013 IBM Corporation
Global Consumer
Products Company
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
Data Explorer’s Role in Big Data Exploration
Explore and mine big data to find what is
interesting and relevant to the business for
better decision making.
Requirements
Data Explorer Examples
•
Explore new data sources for potential
value

•
Mine for what is relevant for a business
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
imperative
•
Assess the business value of unstructured
content
•
Uncover patterns with visualization and
algorithms
•
Prevent exposure of sensitive information
Data Explorer is Search for Big Data.
Accurate
Integrated
Highest level of search relevancy
Powerful search operators
Customizable relevancy
algorithms
Rich connector framework
Connect to 1000s of data sources
Direct integration with leading IBM
products and platforms
Social
360° Insights
Capture tribal knowledge
Annotate search results
Push relevant information to users
See real-time updates of data
Visualize relationship among
entities of interest
Powerful Search
Text Analytics
Proven
Search within documents
Incremental updates to indices
Term position and frequency
determine relevancy
Tight integration with Big Insights
Dynamic textual clustering
Combine structured and
unstructured content
12+ years experience deploying
enterprise class search solutions
for some of the largest customers
on the planet
Scalable
Analyze trillions of records
Enterprise-class infrastructure
Secure
Align with governance models
Field-level document security
Leverage existing enterprise
security models
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Access across
many sources
Dynamic
categorization
Expertise
location
Leveraging
Structured and
unstructured content
Highly relevant,
personalized
results
Refinements based
on structured
information
Tagging and
collaboration
Virtual folders for
organizing content
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Four value pillars represent ROI potential for big data exploration
Leverage
Existing Assets
Improve
Productivity
Eliminate data
silos
Reduce training
costs
Leverage
existing research
and knowledge
Improve staff
retention
Eliminate/retire
unused systems
Improve
collaboration
Capture tribal
knowledge
Extract value
from existing
assets
Eliminate
redundant
projects
Increase Revenue
Reduce Risk &
Improve Compliance
Equip sales and
service staff with
current, accurate
info
Reduce time to
monitor and
comply
Increase upsell
and cross-sell
Push relevant
regulatory
updates/alerts
Reduce sales
cycle
Honor pricing,
NDAs, etc.
Increase
customer lifetime
value
Single version
of the truth
Recommendations
Avoid penalties
Getting started with big data … here are the
steps
Discover
Assess
Collaborate
Leverage
Connect securely to all data sources
Provide unified search and navigation
Surface relationships & themes
Identify the value of the data
Recognize users of the data
Establish context of data usage
Augment the data with user knowledge
Create personalized views of the data
Identify ongoing integration points
Build compelling applications using all of your data
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© 2013 IBM Corporation
Five key big data use cases
Big Data
Exploration
Enhanced 360o View
of the Customer
Security/Intelligence
Extension
Enhanced 360o View
of the Customer
Operations
Analysis
Extend existing customer views
(MDM, CRM, etc.) by
incorporating additional internal
and external information sources
Data Warehouse
Augmentation
Enhanced 360º View of the Customer: Needs
Optimize every customer interaction
by knowing everything about them.
Requirements
•
Create a connected picture of the
customer
Data Explorer Examples
 360°view of customers, partners,
products, suppliers, etc.
 Information from many sources all
in a single view
•
Mine all existing and new sources of
information
 Content and analytics proactively
pushed based on context
•
Analyze social media to uncover sentiment
about products
 Collaboration capabilities
•
Add value by optimizing every client
interaction
 Application framework for rapid
deployment
 Leverage MDM to build line of
business applications
A customer is a puzzle made up of many
pieces
Business Context
Contact Information
Name, address, employer, marital…
Account number, customer type,
purchase history, …
Legal/Financial Life
Property, credit rating, vehicles
Every interaction
requires someone
to piece together
parts of the
puzzle
Social Media
Social network, affiliations, network …
Professional Life
Employers, professional groups,
certifications …
Leisure
Hobbies, interests …
Information about
your customers is
dispersed, forcing
your employees
to extract it pieceby-piece
Individual silos can answer typical questions, one-by-one
Who is this customer?
What products has she
purchased?
What issues has this
customer had in the past?
… but an enhanced 360º
view provides answers in
one application
CRM
DBMS
Support
Ticketing
What is her view of
our company?
Social
Media
Where else has she
worked?
External
Sources
What is available
inventory?
Supply
Chain
How is her company
using our products?
Content
Mgt.
Who is best able to help
this customer?
Experts
Email
Fulfillment
Wiki
Enhanced 360º View answers questions that require multiple systems
What products can I upsell
this customer?
What impact will inventory
have on her?
What marketing materials
should I send?
What should I know before
calling her for renewal?
What’s going on with
this customer TODAY?
How can we increase
engagement with her?
How can we get more
customers like her?
Fusion of data from
multiple systems enables
deeper insights—not just
facts
CRM
DBMS
Support
Ticketin
g
Social
Media
Email
External
Sources
Supply
Chain
Fulfillment
Content
Mgt.
Experts
Wiki
Product offers based on
past purchases and
conversations
MDM ensures consistency
and accuracy
Contact
information from
CRM
Consolidated list of
products owned based on
account affiliation
List of past purchases by
this contact from order
tracking system
Recent conversations
from multiple sources:
e.g., CRM, e-mail, etc.
Master Data Management drives consistency and accuracy in the 360º view
SOURCE SYSTEMS
CRM
Name:
J Robertson
Address: 35 West 15th
Address: Pittsburgh, PA 15213
ERP
Name:
Janet Robertson
Address: 35 West 15th St.
Address: Pittsburgh, PA 15213
Legacy
Name:
Jan Robertson
Address: 36 West 15th St.
Address: Pittsburgh, PA 15213
Master Data
Management
360 View of
Party
Identity
First:
Janet
Last:
Robertson
Address:
35 West 15th St
City:
Pittsburgh
State/Zip:
PA / 15213
Gender:
F
Age:
48
DOB:
1/4/64
Unified View of Party’s Information
BigInsights
Unified
View of Party’s Information
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Streams
Warehouse
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 fastmoving 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
Business Benefits
Capabilities
Phase I
Phase II
 Connect to enterprise &
web content
 Integrate MDM
 Create customer/product
dynamic pages




Phase III
Integrate collaboration tools  Integrate recommendations
Reveal insights
 Add additional content
sources
Build out user preferences
 Federate analytics
Retire redundant systems
Promote up-selling &
cross-selling through
dynamic recommendations
Enable positive customer outcomes
Increase savings by retiring redundant systems
or moving to cheaper storage
Reduce or re-purpose head count through increased productivity
Provide consistent view of products & customers to improve ALL customer interaction
Productivity
Revenue
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?
 Have you considered the
impact on your business of
not providing a single point of
access for all customerrelated 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?
 How would a complete view
of the customer enhance
your line of business? Are
there specific business
outcomes you are looking
for?
 Are you able to combine your structured & unstructured data together to
run analytics & create a more consistent view of your customers?
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
[email protected]