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 MillionFinancial

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 AnalysiSource: 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

archiveTrusted 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 insightDecision

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


© 2014 IBM Corporation11© 2013 IBM Corporation

So how does IBM InfoSphere Data Replication 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

UseInfoSphere 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


Scenario 2 – The solution InfoSphere Data Replication for data warehouse optimization

UseInfoSphere Data Replication to feed operational mainframe and distributed data in real-time to your enterprise data warehouse.

Because InfoSphere Data Replication uses parallelism and proprietary algorithms to supercharge data delivery for an active data warehouse.

WhenYou 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 timeto 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

Scenario 3 – The solution InfoSphere Data Replication and InfoSphere Streams for operations analysis

UseInfoSphere 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.

WhenYou want to uncover fraud, upsell opportunities or perform operations analysis.

Low impact, high

performance data capture



FinancialServices

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% highersuccessful transaction rate for high-value customers through simplified processes

75% fasterreport 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 InfoSphere Data Replication change data capture technology with InfoSphere BigInsights

Twitter: @IBMDataRep

http://www-01.ibm.com/software/data/replication/



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ibm infosphere data replication for big data

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