IBM InfoSphere Data Replication for Big Data

© 2014 IBM Corporation
IBM InfoSphere Data Replication
for Big Data

© 2014 IBM Corporation2
Disruptive forces impact long standing business models across
industries. Agility is key to survival.
“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

$8 Million
Financial
Telco
$4.6 Million
24 x 7 operations … will continue to
drive demand for replication as a
key element of a high-availability
strategy for mission-critical databases.
IT$3.3 Million
However agility cannot be at the expense of availability
Source: IDC WW Data Development and Management Tools Software 2010 Vendor and Segment Analysi
Source: Robert Frances Group 2006, “Picking up the value of PKI: Leveraging z/OS for Improving Manageability,
Reliability, and Total Cost of Ownership of PKI and Digital Certificates.” (*)
Cost of 1 hour of downtime during
core business hours

How do you balance the
need for agility with
availability?

Information Integration & Governance
Exploration,
landing and
archive
Trusted data
Reporting &
interactive
analysis
Deep
analytics &
modeling
Data types Real-time processing & analytics
Transaction and
application data
Machine and
sensor data
Enterprise
content
Social data
Image and video
Third-party data
Operational
systems
Actionable
insight
Decision
management
Predictive analytics
and modeling
Reporting, analysis,
content analytics
Discovery and
exploration
By using a next generation architecture for delivering insights

The T=tale of a Large Telco: The challenge
Benefits

The tale of a Large Telco:
The solution: InfoSphere Data Replication + CRM
Benefits
All while maintaining peak system performance

“IBM InfoSphere Data Replication
gives us real-time insight into our
operations, helping us to attract new
business and maintain our
leadership position.” – A large US
Telco

Organizations use InfoSphere Data Replication
because it captures changed data from database logs for minimum latency and impact
Minimum impact
• No additional hardware requirements
• Minimal network bandwidth usage
• No application or schema changes
• Negligible impact on production
systems
• No batch window requirements
Minimum latency
• Transactions transformed and sent to
target as they occur
• Scales with increasing data volumes
• Performs with shrinking processing
windows
Simple to use
• Easy wizard driven installation
and set up
• Easy configuration with GUI,
scripting or API
• Easy monitoring with full function
dashboard

InfoSphere Data Replication
Real-time, low impact, trusted data delivery for the enterprise
• Heterogeneous Data Delivery • Conflict Detection and Resolution
• Drag and Drop Transformations • Internationalization • Built in Monitoring

So how does IBM
enable faster insights from
Big Data?

In
ways

Scenario 1 – The problem
Real-time analysis that doesn’t impact transactional systems
Retail
A mid-sized company wants has
access to lots of potentially valuable
data that is dormant or discarded due
to size/performance considerations.
It’s unclear to them what of the data
that isn’t discarded should be
analyzed and what is just noise.

They decide to use Hadoop to sift
through potentially large volumes of
unstructured or semi-structured data
to capture the relevant information
that needs to be combined with
transactional data before sending
it to a warehouse.
How do they ensure they
don’t impact the transactional
source systems?
Retail
Scenario 1 - The problem (continued)
Real-time analysis that doesn’t impact transactional systems

Scenario 1 – The solution
InfoSphere Data Replication for Big Data Exploration on Hadoop
Use
InfoSphere Data Replication’s
HDFS apply to send data in real-
time to Hadoop distributions like
IBM InfoSphere BigInsights,
Cloudera and Hortonworks.
Because
InfoSphere Data Replication’s
Hadoop integration allows you
to gain new insights quickly
and easily.

Scenario 2 – The problem
Inability to access real-time transaction data in multiple formats
Scotiabank’s clients required the
ability to access real-time balance
and transaction data on demand and
in multiple formats. However, their
architecture could no longer meet
business requirements.
Banking

InfoSphere Data Replication for data warehouse optimization
Use
InfoSphere Data Replication to
feed operational mainframe and
distributed data in real-time to
your enterprise data warehouse.
Because
uses parallelism and
proprietary algorithms to
supercharge data delivery for
an active data warehouse.
When
You want to make better
business decisions faster
based on up-to-the-second data.

Scenario 2: The result
Dramatic time reduction to deliver reports to support timely, accurate decisions
99%
Reduced time
to deliver
reports
Reduced time
to deliver
reports
“The dramatic increase in reporting
usage that we have seen since
the rollout of the solution confirms
the value that our clients place on
convenient access to timely, accurate
information about their business. ”
Senior Vice President, Cash Management and Payment Services,
Global Transaction Banking, Scotiabank

Scenario 3: The problem
An organization needs to increase customer satisfaction
Telecom
A telco wants to provide a new service to
its customers to increase customer
satisfaction. It wants to allow mobile phone
subscribers to specify a personal limit of
costs per month. When their balance nears
or exceeds this maximum, the customer
receives an email and text message
letting them know.

Telecom
The information the telco needs to
provide this service is in their heavily
used billing system built on a
relational database. Rather than
rewriting it, they can use InfoSphere
Data Replication to detect changes
and InfoSphere Streams to
handle the events and
trigger the email and
text messages.
Scenario 3 - The problem (continued)
An organization needs to increase customer satisfaction

Real-time processing & analytics platformData types
Transaction and
application data
Machine and
sensor data
Enterprise
content
Social data
Image and video
Third-party data
INFOSPHERE DATA
REPLICATION
INFOSPHERE
STREAMS
Enterprise
class stream
processing &
analytics
Actionable insight
Decision
management
Predictive analytics
and modeling
Reporting, analysis,
content analytics
Discovery and
exploration
InfoSphere Data Replication and InfoSphere Streams for operations analysis
Use
InfoSphere Data Replication to
detect changes in real-time and
InfoSphere Streams to apply
stream analytics for complex
event processing.
Because
IBM is the only vendor with a
mature streaming analytics
platform that includes the
capability to capture data from
anywhere.
When
You want to uncover fraud,
upsell opportunities or
perform operations analysis.
Low impact,
high
performance
data capture

Financial
Services
Government
Retail
Telecom
Other industry-specific applications
Multi-channel sales.
Real-time inventory.
Gift registry updates.
Verifying benefit
eligibility.
Security threat
detection.
Mobile banking.
Fraud detection.
First call resolution.
Cross-sell/up-sell.
Customer retention.

• IBM® InfoSphere® Data Replication
• IBM InfoSphere Information Server
• IBM InfoSphere DataStage®
• IBM® PureData™ System for Analytics, powered by
IBM Netezza®
• IBM Global Business Services® – Business
Consulting Services
• IBM Business Partner iSoftStone
A Beijing-based mobile payments processor
uses big data and analytics to maximize insight from client transaction data
20% growth
annually through improving
customer insight
Solution components
Business challenge: Growing volumes and varieties of data have made it
increasingly difficult for businesses to gain insight from customer transactions.
This payment-processing company based in Beijing ingested but could not gain
value from the massive amounts of data from payment transactions between its
business customers and their consumers.
The smarter solution: Using a big data and analytics solution, the company can
now identify its most valuable customers to offer them new products and services
first, helping grow its business. It can analyze how consumers are using its
payment services by factors such as region, time and type of business, helping
continually optimize and target its services. The solution also helps the company
grade and segment its business customers by risk propensity and offer low-risk
customers simplified risk management rules that speed transaction processing.
Using the analytics solution to gain value from its data helps the company
understand its customers’ real needs.
192% higher
successful transaction rate
for high-value customers
through simplified processes
75% faster
report generation speed

For more information
 Website: http://www-
01.ibm.com/software/data/repl
ication/
 Paper: Derive actionable, real-
time insight from your big
data with data replication
 developerWorks article: Use
change data capture technology
with InfoSphere BigInsights
 Twitter: @IBMDataRep

• © IBM Corporation 2014. All Rights Reserved.
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