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Key Reasons to Move the Data Warehouse to the Cloud


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While the established data warehouse excels at core analytics, enterprises need to be more agile than ever before because of the Internet of Things.

In a recent DTBA roundtable webcast, Joe Caserta, president and CEO of Caserta Concepts, and Wendy Lucas, program director for IBM Data Warehouse marketing at IBM, discussed the benefits of data warehousing approaches in the cloud.

Traditional data warehouses consist of data models, extract, transform, and load processes, and data governance, with BI tools sitting on top.  “It has become very top heavy and what we need to do is start evolving to handle processes differently to become agile,” Caserta said.

Instead of doing things the old way, which includes structuring, ingesting and analyzing, Caserta suggested that enterprise data warehouses need to flip the paradigm and ingest, analyze, and structure by utilizing the cloud, data lakes, and polyglot warehousing, Caserta explained.  “We need to think of our data warehouse not as a single technology but as a collection of technologies.”

Moving to the cloud provides several advantages, including a reduction of upfront capital investment, faster speed to value, and greater elasticity, Caserta said.

This approach also removes barriers from data ingestion and analysis, along with providing storage and processing for all data and feature tunable governance.

Tapping into Hadoop is also an option that can help move data through its warehouse when in the cloud, Caserta noted. “The takeaway from this is really to stop thinking about a single data base solution; the data warehouse has evolved to move to the cloud,” Caserta said.

IBM has an integrated set of capabilities for the data warehouse and Hadoop to create this ecosystem, Lucas added. “It’s fundamentally a platform that will help you enable a true hybrid data warehouse solution,” Lucas said.

To view a replay of this webinar, go here


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