Offload the Data Warehouse in the Age of Hadoop
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The data warehouse is likely your most expensive CAPEX and OPEX expense -- and if you haven't checked your warehouse capacity & utlization, it's likely running low. ...
The data warehouse is likely your most expensive CAPEX and OPEX expense -- and if you haven't checked your warehouse capacity & utlization, it's likely running low.
Thanks to Big Data & the advent of Hadoop, it no longer makes economic sense to process bulk data transformations (often called ELT -- Extract, Load & Transform) using data warehouse compute.
Join others who have already offloaded storage & processing from Teradata, Oracle, Netezza & DB2 onto Hadoop to save millions by avoiding upgrades!
Offloading makes your data warehouse run faster for critical end-user queries & frees up storage for Big Data -- but how do you make the jump? What transformations are costing you the most? What data in your warehouse are you not using?
Learn how you can:
Find dormant data. Up to 50% of the data in your data warehouse and data marts is never queried by business users -- but you need the right tools to find it.
Identifty transformations to offload. Quickly find out which ELT transformations you should shift to Hadoop.
Manage data movement & processing to Hadoop. Easily collect, process & distribute data in Hadoop with an intuitive graphical user interface. No coding or scripting required.
Deliver faster Hadoop performance per node. Find out how capabilities in the Apache core can help you accelerate batch Hadoop processing by up to 30% on existing hardware with no code changes, & without risk.
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