For generations, enterprises have used IBM data management products to store and manage transactional and analytical data. They rely on IBM database products like DB2 Mainframes, IBM Informix, and DB2 on LuW to store mission critical data. A huge amount of analytical data is also managed by IBM analytical databases like DB2 and IBM Netezza.
With Netezza moving into its sunset phase, Databricks is a modern, state-of-the-art alternative for enterprises. The challenge is to ensure the operational data travels in an easy, effective, and seamless way to the cloud. Databricks Lakehouse helps companies consolidate ETL, streaming, BI, and data science workloads onto the same platform, by combining the performance and governance of the data warehouse with the flexibility of the data lake.
In the video presentation below, learn from experts how to architect modern data pipelines to consolidate data from multiple IBM data sources into Databricks Lakehouse, using the state-of-the-art replication technique—Change Data Capture (CDC).
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