SAP HANA in-memory analytics: What’s it all about?

Clive Margolis sums up the in-memory analytics scene:

A problem facing business intelligin-memory-analyticsence users is the sheer volume of data you need to crunch in order to analyse it down to useful information.  Until recently the BI team’s response to this problem would probably be to summarise more data in the data warehouse, which could well involve some redesign of the data warehouse itself.

In-memory analytics is another way to solve it.  Largely driven by the business users themselves, products such as SAP HANA and QlikView stream the data into high-speed RAM and give you a toolset to roll it into the right shape to get you the answers you need.

Data is shown in “views”, on-screen dashboards or other graphical representations, and can be selected with various forms and drop-down menus.  Because of the intensity of processing required, in-memory products such as SAP HANA are often partnered with purpose-built hardware platforms such as Oracle Exadata machines.



Matt Floyd‘s insight:

Advantages and disadvantages of in-memory BI tools, such as Qlikview, Tibco Spotfire, and SAP Hana. Timely, as in-memory appears to be gaining steam.

See on


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