This presentation is from TDWI's event in Boston during the summer of 2014. IBM InfoSphere BigInsights is IBM's enterprise grade Hadoop offering. It combines the best of open-source Hadoop, with advanced capabilities including Big SQL that clients can optionally deploy to get to market faster with a variety of big data and analytic applications.

1. © 2014 IBM Corporation
Getting Started with Big Data
Five Game Changing use cases
Gord Sissons
IBM InfoSphere BigInsights

2. © 2014 IBM Corporation2
annual Internet traffic by 2016
Internet of Information
e-mails per minute
Internet of Engagement
users of social media today
by 2017
Internet of Things
connected devices today
by 2020
Big Data is every where we look

3. © 2014 IBM Corporation3
Driven by new technological capabilities and
transformative economics
• Vertical infrastructure for DW/BI
• What data should I keep?
• Design schemas in advance
• ETL, down-sample, aggregate
• What reports do I need?
The Old Way The New Way
• Distributed data grids
• Keep everything just in case
• Evolve schemas on the fly
• Extract knowledge from raw data
directly
• Test every theory, model “what-
ifs” on the fly
A new way of thinking

4. © 2014 IBM Corporation4
Big Data Objectives
Customer-centric outcomes
Operational optimizations
Risk / financial management
New business model
Employee collaboration
49%
4%
18%
15%
14%
Customer-centric
outcomes
Other
objectives
Total respondents n = 1061
Top functional objectives identified by organizations with active big data pilots or implementations. Responses have
been weighted and aggregated. - http://www-935.ibm.com/services/us/gbs/thoughtleadership/ninelevers/

5. © 2014 IBM Corporation5
Data Warehouse Modernization
Integrate big data and data warehouse
capabilities to increase operational efficiency
Operations Analysis
Analyze a variety of machine
data for improved business results
Big Data Exploration
Find, visualize, understand all
big data to improve business
knowledge
Enhanced 360o View
of the Customer
Achieve a unified view,
incorporating many data sources
Security/Intelligence
Extension
Lower risk, detect fraud and
monitor security in real-time
Five Big Data use cases

6. © 2014 IBM Corporation6
66
City of Dublin; City-wide
traffic awareness system,
enhance incident response
Need
• A cost effective solution to improve traffic
awareness system
• Accuracy in event detection, inferring traffic
conditions and predicting bus arrival times
• Challenge is to correctly analyze GPS data -
high throughput, difficult to capture
Benefits
• Monitor 1000 busses across 150 routes daily
• Analyzes 50 bus location updates per second
• Collects, processes, and visualizes location
data of all public transportation vehicles
6
Operations Analysis
http://www-03.ibm.com/press/us/en/pressrelease/41068.wss

7. © 2014 IBM Corporation7
Campaign launch time
80% reduction
Campaign performance driving ROI
70% improvement
Reduction in analytic processing time
90% reduction
Reduced churn through personalized
loyalty campaigns, increased ARPU
Celcom Axiata
Enhanced 360 view of the customer
http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=C192500J38882P30

8. © 2014 IBM Corporation8
© 2013 IBM Corporation
Increases knowledge worker
efficiency saving USD36 million
per year in one department alone.
 80,000 internal users, 40,000+
external users
 Accessing dozens of separate data
sources throughout the enterprise
 Single-point of data fusion for all
employees
 Improved operational performance for
multiple departments
 50 additional aircraft in service with no
staffing increase
Global Aerospace
Manufacturer
Big Data Exploration http://www.airbus.com/presscentre/pressreleases/press-release-
detail/detail/airbus-and-ibm-to-help-aircraft-operators-optimize-
fleet-management-and-operations/

9. © 2014 IBM Corporation9
Major energy company uses
stream data to monitor ice-
flow movement in real time
Need
• Acquire streaming data from a variety of
sources to analyze atmospheric conditions
• Thousands of data points per second
• Analyze massive volumes of data
continuously at rates up to petabytes per day
• Adapt to rapidly changing data forms and
types
• Leverage sub-millisecond latencies to
respond to events and trends as they unfold
Benefits
• Anticipates saving roughly USD 300 million
per season by reducing mobilization costs
associated with needing to drill a second well
• Estimates savings of USD 1 billion per
production platform by easing design
requirements, optimizing rig replacement and
improving ice management operations
9
Operations Analysis
http://www-03.ibm.com/software/businesscasestudies/us/en/corp?synkey=C192500J38882P30

10. © 2014 IBM Corporation10
Analyzed behavior patterns
25% increase in email opening
rate
Improved wait times
Data analysis performance
increased by 40x
Reduced IT workload
ETL development resources
reduced by 50%
Constant Contact
Data Warehouse Modernization
http://www.ibmbigdatahub.com/video/ibm-big-data-solutions-redefining-e-mail-marketing-success-constant-contact

11. © 2014 IBM Corporation11
Time to value matters
Just because you can build a solution from
scratch doesn’t mean you should!

12. © 2014 IBM Corporation12
Information Integration & Governance
Systems Security
On premise, Cloud, As a service
Storage
New/Enhanced
Applications
All Data
What action
should I
take?
Decision
management
Cognitive
Fabric
Landing,
Exploration
and Archive
data zone
EDW and
data mart
zone
Operational
data zone
Real-time Data Processing & Analytics What is
happening?
Discovery
and
exploration
Why did it
happen?
Reporting and
analysis
What could
happen?
Predictive
analytics and
modeling
Deep
Analytics
data zone
Data Warehouse Modernization

13. © 2014 IBM Corporation13
IBM InfoSphere® BigInsights
 100% standard Hadoop
 Extensive capability
 BigSheets, Big SQL, Big R
 Pre-built Accelerators
 Streaming Analytics
 Breakthrough performance
 POSIX file system
 Extensive solution ecosystem
Compressed time to business value

14. © 2014 IBM Corporation14
Learning more
http://BigDataUniversity.COM
http://BigDataHub.COM

15. © 2014 IBM Corporation15
Learning more
http://Developer.IBM.COM/Hadoop
http://Developer.IBM.COM/Streams

16. © 2014 IBM Corporation16
Thank you!
@GJSissons
gsissons@ca.ibm.com

17. © 2014 IBM Corporation17
For Discussion
What are the critical success
factors associated with ensuring
that a big data or analytics initiative
delivers a successful business
outcome?

18. © 2014 IBM Corporation18
IBM’s Research
Analytics: a blueprint for value.
Converting big data and analytics
insights into results
http://www.ibm.com/services/us/gbs/
thoughtleadership/ninelevers/