The document outlines five transformative use cases of big data, highlighting the shift from traditional data management to more dynamic, continuous analytics. It emphasizes the integration of big data with existing data warehouse capabilities to enhance operational efficiency and customer insights. Additionally, it presents examples of successful implementations across various sectors, demonstrating significant cost savings and improved performance metrics.

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/