Big Data Camp LA 2014, From Big Data to Big Insights by Alex Liu of IBM

1. © 2014 IBM Corporation
From Big Data
to Big Insights
Dr. Alex Liu – Big Data Scientist
June 14, 2014
BDCamp-06-14-2014-1

2. © 2014 IBM Corporation
Big Data is hot
Cost effectively manage
all available data
unstructured, structured, streaming
ERP
CRM RFID
Website
Network Switches
Social Media
Billing

3. © 2014 IBM Corporation
Know Everything about your Customer
Analyze all sources of data to know your customers
as individuals
Instant Awareness of Fraud and Risk
Analyze all available data, detect fraud and
manage risk in real-time
Innovate New Products at Speed and Scale
Capture all sources of feedback and analyze vast
data to drive innovation
Exploit Instrumented Assets
Predict and prevent maintenance, develop new
products & services
Big data has great potential, and can impacts every aspects …
Creates customized offers up
to 125x faster with better results
Reduced processing time in half
Loads hurricane data in seconds
and performs risk analysis in
near real-time for greater
reliability
Identified fraud which previously
went undetected
Capabilities Outcomes

4. © 2014 IBM Corporation
Many organizations are already enjoying the power of
using big data for big insights leading to great results
• Big Data Strategy
• Business Analytics
Rapid and data-driven decisions
consistent across the organization
Business
Value
Use Over Time
Top performers are
more likely to use big
data analytic approach*5.4x
Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010.
*within business processes

5. © 2014 IBM Corporation
Business-Centric Big Data Analytics Enables You to Start With a
Critical Business Pain and Unleash the Power of Big Data
 “Big data” isn’t just a technology—
it’s a business strategy for
capitalizing on information
resources
 Getting started is crucial
 Success at each entry point is
accelerated by products within the
Big Data platform
 Build the foundation for future
requirements by expanding further
into the big data platform

6. © 2014 IBM Corporation
Big Data Analytics is a process
4Es – Equation – Estimation – Evaluation - Explanation

7. © 2014 IBM Corporation
CASE I: Predicting Customer Churn with Big Data Analytics
20%
Reduction
in Churn
7x
Improvement in
XML
Processing
Time
Customers Most
Likely To Leave
(and Why)
Dropped Calls
Calling Patterns
(Big Data)
Rate Plans
Integrate/Cleanse/
Deduplicate
Data
Warehouse
Predictive
Modeling
Why do people leave and how can you intervene
before it’s too late?
Ongoing insightMaster
Data
Management
Key Capabilities
• Customer Analytics
• Predictive Analytics
• Data integration with
Common Metadata
• Master Data Mgmt
• Big Data
• Warehouse Scalability
• Compression and
Archiving

8. © 2014 IBM Corporation8
CASE II: Big Data Audience Insight Analytics enables rich audience
analysis and a better customer acquisition
Capture, integrate and analyze
data
Combine data sets to measure
content consumption and create
audience profiles
Make insights operational to
drive business decisions
Structured Unstructured
Hadoop
System
Stream
Computin
g
Data
Warehous
e
Accelerators
Information Integration &
Governance
IBM Big Data Platform
 Location
 Gender
 Occupation
 Influence
 Interests
analytics
Programming
Distribution
Marketing
Ad Sales

9. © 2014 IBM Corporation
CASE III: Improving Decision-making for Loan Origination
Approval
Denial
Fast Track
Collaboration
Existing
Customer
Details
Real-Time Data
Gathering
External
Policies
Automated
Scoring/Pricing
Credit
Monitoring
Credit
Monitoring
How can you maximize approval rate while minimizing risk?
6 Days
to
5 seconds
new loan
processing
Key Capabilities
• Content Analytics
• Advanced Case
Management
• Master Data Mgmt
• Business Rules
• Integrated
Collaboration
Master
Data
Management

10. © 2014 IBM Corporation
CASE IV: Fraud Modeling with Big Data
Big Insights Data
Business Vocabulary
Name,
Address,
Medical
condition
Party
Contact point & Preferences
Claim
Communication
Fraud type
Assessment & Condition
Standard Text &
Comms
Risk factor score
Claim fraud assessment
Task
Atomic Warehouse Data
industry shared database
Scan all paperwork(quotations, repair invoices,
previous claims by insured or by another insured
based on chasis, vehicle registration to
ascertain history and condition of vehicle
involved in accident
Claim Fraud type
Claim fraud
Claim fraud condition
Claim fraud investigation
Professional fraud exclusion clause

11. © 2014 IBM Corporation
Thank you