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I was recently interviewed by Charlie Knapp for an article in Quest’s Q&A Magazine titled “How Do You Extract Strategic Value from Big Data?” No surprise that I was enthusiastic in my response! 

As the concept and reality of big data finds its way into organizations, businesses that are trying to get value from their big data problem with fancy (often expensive) new hardware are running a big risk. New hardware may get you a lot of data faster, but it won’t actually make that data work for you. The article is all about understanding big data, what it does and doesn’t do, and includes some great approaches and examples for how to get beyond data to the value.

Here’s a list of key takeaways from the article:

  1. Organizations should be able to tie any big data project to their strategy
    When you're embarking on a big data project, it’s crucial to know what your company is trying to achieve. Once you know this, you can determine what would help you measure your performance toward that strategic goal. Perhaps you have data that would help you predict your future performance? Or maybe you have a variety of supporting performance indicators that lend context?  In short, data for the sake of data serves no purpose, it should always be tied to a larger goal.
  2. Balance cost with value
    Don’t forget to look for quick wins. Some questions require such substantial effort to obtain them from the data, it might make sense to give those a lower priority or maybe a secondary validation to make sure that they're worth it.
  3. Small answers can lead to big value
    You could get more strategic finance value from a handful of small changes rather than one big change. Big data can help you identify those small things. Make sure you consider this as one of your goals.
  4. Get the right people ready
    Working with big data, and the technologies that support it, often requires different skill sets and strengths. The Q&A Magazine article includes a description of the abilities your team should possess to tackle this. That includes an analytical mindset, creative skills, statistics and computer science experience, and business and communication abilities.

It is so tempting to just look for technology that magically gives you value from big data, but the real message here is that technology for the sake of technology won’t get you value – in fact, it just costs you money. Check out Charlie Knapp’s full article here!

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