Are You Ready for Big Data?

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There have been some interesting articles over the past month in the space of big data. Three topic trends are emerging and they paint a picture of an industry searching for its footing.

Follow the Money

Investors continue to put money into development of the technologies and tools that are allowing big data ambitions to be realized. It is not a feeding frenzy, but there is a steady stream of funding being targeted for big data startups. It is clear that a perception of potential is held be investors. There does seem to be a logic that big data is really upon us. In fact, I contend that big data has been with us for at least the last decade, we just didn’t recognize it was there. Is it really a new type of data, or is it looking at old data a new way? The reality is that it is probably a bit of both. Transactions from processes like social media and the emergence of sparse data are relatively new, but the existing base of data has long held valuable information that we did not know how to extract.

Academics are Adapting

Can we handle big data? That question is less about storage and more about talent. In order to fill the talent gap a number of institutes are creating courses and degrees focused on analytics of big data. It is a new discipline. One that is more anticipatory, meaning it is still formative. I find it encouraging that institutions are taking a hard look at big data and seeing that it demands a different approach than traditional MIS oriented courses. It will take time for the methods and structures to evolve. The practitioners who graduate from the programs will be the ones developing that methodology and having a profound impact on how big data is used in the future. They are the talent that the investors are counting on to make big data a market product that generates revenue.

Job Titles are Evolving

Having startup funding and talent armed with advanced analytic skills is only part of the solution. Big data is an enterprise asset, whether for-profit, not-for-profit, or government. That means that it is only “real” if it is recognized within the operating model of the enterprise. There are various levels of recognition. Big data responsibility can now appear as a line item in a job description with specific analytical skills as a requirement or it can be elevated to an individual job title that will have a more comprehensive big data definition. The real recognition will be when an executive position is appointed that has responsibility for the governance, architecture and operations of a big data environment. Just where the big data responsibility appears reflects the individual enterprise’s perceived value of the discipline. The higher the level of the staff and the more talent that is aligned to the delivery will indicate how important and strategic big data is to that enterprise.

Still at the Starting Gate

Investment, talent training and organizational awareness are all conspiring to make big data a real discipline in the future. Are we there right now? I would say not yet, but the runway is defined and almost ready. In the past I have counseled you to think about where big data is going to play in your enterprise, but from a technical point of view only. Now it is important to add an operating model element to that strategy. Where will you place responsibility for big data and the analytics that come with the territory? How will you staff your needs – in-house or third party? Most important, what is the value to the business that you want to provide through big data analytics? Please let us know your thoughts, questions and plans for Big Data  in the comment area below.

Jerry Gentry is a research analyst for Nemertes Research. To get more useful enterprise class data center management strategies and insight from Nemertes Research download the Q3 Data Center Knowledge Guide to Enterprise Data Center Strategies, compliments of Vantage Data Centers.

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  1. Data101

    Jerry, good article. One solution that can help turn big data challenges into big opportunities is HPCC Systems from LexisNexis which provides for an efficient low cost one-stop solution for BI and analytics needs. This open source enterprise-ready solution is comprised of a single platform that is easy to install, manage and code. Their built-in analytics libraries for Machine Learning and integration with other open source tools like Pentaho provide companies with an end to end solution for ETL,data mining and reporting. For more info visit: hpccsystems.com