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Making Big Data Manageable

A single day does not go by without a healthy discussion or debate on the meaning or impact of the term ‘big data.’  It is quite comical in one sense, and quite inspiring in another. We are all intrigued by this concept of having access to information so that when we get THE question, we will find THE answer. And hopefully the answer is more than “42!” (for those who may not be familiar with the reference, please take a pause and read the classic “Hitchhiker’s Guide to the Galaxy” by Douglas Adams).

These past few weeks were no different. I was fortunate to have the opportunity to present at Informatica World and attend EMC World recently. While Informatica is leading the charge for data integration, they are also taking a thought leadership position in how to conceptually view an organization’s return on its data. Combining aspects of value, cost, and the impact of big data, I saw it as an elegant way to say – hey, look – you can keep all the data you want to derive value, but there is a trade-off. There is ultimately a cost. That cost can be measured hundreds of different ways – but there will be consequences. So we have to prioritize and put controls in place to maximize ROI.

Now let’s say this data – this big data set – can provide incredible value – but only for today or for a week. Then, after that shelf life, the value drops. Then what?

That is where information lifecycle management (ILM) fits in. If upon creation, you assign a time-based value model associated with that class of data, you can now optimize your cost structure. So it’s not just a one-time calculation, it occurs throughout its lifecycle. Many attendees of my sessions commented on how pleased they were to see so much of Informatica’s ILM portfolio integrated with the big data messaging. By making big data cost-effective, it becomes more manageable.

This was just one of the dimensions that made the event so insightful and worthwhile – but one I want to keep on top of mind. ILM is no longer just about tiered storage – but about maximizing value and minimizing cost and risk of information. Production apps, test and development copies – on premises or off – ILM applies to transaction processing sources, legacy applications, data warehouses, and especially data stored in a Hadoop cluster.

After taking a brief pause and returning back to Vegas to catch EMC’s event, I was blown away by the innovations and new product releases – and guess what? They announced 42 new products – while mostly related to storage, EMC is making it easier to store, backup, archive and analyze big data.  And because EMC resells Informatica ILM solutions, and Informatica is making big data more manageable, there is plenty of opportunity to accelerate their return on big data.

There is huge potential here for Informatica to take its’ forward thinking initiatives with big data and its’ investment in the ILM portfolio to help organizations make the math work – even if the answer is ultimately 42.

 

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