This week, Martin and Chris talk to Krishna Subramanian, President and COO at Komprise.  We mentioned the Komprise technology back on episode #75 (It’s ILM All Over Again) as part of a discussion on managing the movement of files to and from archive storage.  Krishna joins this discussion to fill in some background on the challenges of managing unstructured data, including how to implement solutions with as little lock-in as possible.

Why do we need to manage data in the first place?  With around 75% of all data having no access in over 12 months, there’s clearly a cost saving for primary storage.  This extends further into eliminating backup copy duplication.  Of course, efficiencies can also be gained in performance as well as converting capital costs to operational ones.

More details on Komprise can be found at https://www.komprise.com.

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Timeline

* 00:00:00 – Intros

* 00:02:00 – Where is new data coming from?

* 00:03:00 – What problems exist with unstructured data?

* 00:05:00 – Unstructured – just file and object?

* 00:06:30 – Start with visibility of the data

* 00:09:00 – Does it make sense to use file virtualisation (like DFS)?

* 00:11:00 – End users need to know that data has been archived

* 00:12:30 – Stubs or links?  What’s the difference and benefits?

* 00:15:00 – How is file searching affected?

* 00:16:00 – Data mover VMs scale to manage data movement in Komprise

* 00:18:00 – Does individual file movement work with all types of data?

* 00:21:00 – Where do we keep our metadata – inception?

* 00:24:00 – Is archive the slippery slope to moving to the public cloud?

* 00:26:30 – Do Opex charges encourage users to delete data?

* 00:29:00 – What strategies are being taken to deal with data sprawl?

* 00:31:30 – Continuous data optimisation is an eventuality

* 00:33:40 – What is the future of data management?

* 00:35:20 – Wrap Up

Related Blogs and Podcasts

* #75 – It’s ILM All Over Again with Chris Mellor

* #65 – Challenges in Managing Unstructured Data with Shirish Phatak

* The $2 billion Gamble on Data Management

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