About the client: Ujjivan is a leading Microfinance company in India and have recently been awarded the Small bank license by the Reserve Bank of India.
Business Challenges: The client wanted to gain better insights from their customer data. Multiple legacy systems and complex IT infrastructure meant that they were not able to glean timely insights. In addition the new banking license necessitated appropriate Data Governance frameworks to meet future compliance requirements and to increase the business trust in the underlying data and information systems.
Solution: The proposed solution using IBM InfoSphere will connect to various databases, capture changes at source (CDD) and perform complex ETL, and populate the Data mart. The Change Data Delivery option reduces the number of records moved/processed on the ETL server and help meet the business defined SLAs. Cognos and SPSS were used for Reporting and Predictive analytics. The Data Dictionary and Data lineage options were recommended to enable the business user to track the journey of data from reports all the way to the source systems, thereby increasing the trust in Analytics.
  • Achieved business SLAs:With CDD enabled, parallel data transformation, the ETL processing time was reduced from 16 hours to 4 hours.
  • Improved Governance and Trust:Significantly increased the process and trust that the users had in the IT systems and Data.
  • Improved Productivity: With less data issues to deal with, the business spends more time in analyzing data and gleaning insights
  • Future Proof Investment: Common Meta data layer enables seamless integration with future tools and capabilities such as Data Quality, MDM and Smart Archiving
  • Increased up-sell/cross-sell opportunities–The timely delivery of data into the mart for reporting and the predictive models enables substantial increase in revenue and paves way for future growth
Technology: IBM Information Server, Change Data Delivery, Information Governance Catalog / Glossary (IGC)
About the client: One of the Leading payment solutions provider in India
Business Challenges: Client had undertaken an initiative to implement Cloudera based Data Lake and were facing huge challenges in the acquisition of data from their mainframe applications based on Z/OS as well as from dozens of satellite applications based on Oracle. Z/OS being proprietary in nature did not allow for easy access of data. Client needed a sophisticated solution to extract data in real-time from not only mainframes from also various applications and store them in Cloudera. Client wanted to leverage native Hadoop capabilities for business intelligence reporting as well as for Predictive Analytics
Solution: IBM CDC was used to extract changed data from mainframes as well as from Oracle RDBMS, these data were then fed to a Kafka cluster and then posted to Cloudera. IBM BigIntegrate jobs were used to process data on Cloudera to generate relevant output data for Business Intelligence and Analytics. As part of the engagement governance catalog was also configured to track technical assets and provide end-to-end lineage.
  • Real Time Visibility: Real-time replication of data from various source systems to Cloudera (Data Lake)
  • End-to-End Automation: Leveraged native Hadoop capabilities through IBM products to process data to perform transformation and speed up processing of terabytes of data
  • Streamlined MIS: Enabled day to day operational reporting
  • Enabled Analytics: Supported downstream Analytics Users for model building with near real-time data
Technology: IBM CDC, IBM BigIntegrate (DataStage, QualityStage, Governance Catalog)