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analytics program enablement for growth-mindset organizations

Data Analytics: Don’t Get Lost in Buzz Words

buzzwordsBuzz words dominate data discussions. From the ubiquitous “Big Data” term to excited discussions about SQL and Hadoop, buzz words are tossed about like so many magic words. The results are often as underwhelming as one might expect from someone running around yelling the word “Abracadabra” and expecting something to happen.

A recent ZDNet¬†interview with Lars Hard of Expertmaker and Jeff Cotrupe of Frost and Sullivan almost said it all with the article’s title (click and have a look).

Beyond the very real need to cut through the hype, there are some excellent points being made in the article. For example, there are multiple types of data. There’s also the reality that the majority of the data that any organization sits on is pretty much worthless. Finding the data that you actually want to work with is a vital step in the process of putting that data to good use, and it is one that many companies simply ignore.

Furthermore, data projects should be customized for each and every organization. It’s not enough to simply ram your data through a vendor’s algorithm. Why?

  • Every company runs a little bit differently. UPS and FedEx both deliver packages, but that does not mean they both do everything the same way.
  • Your most pressing business question may not be the same as another company’s most pressing business question–and you want to tackle the most pressing questions first, so that you reap the most benefit from your predictive modeling efforts.
  • You may or may not need to buy additional data from another source until you’ve set your unique targets. Relying on a vendor’s perception of what you “need” is a good way to waste money due to the inevitable conflict of interest between your organization and the vendor’s aims.

The buzz words are so exciting to everyone because there are high-value, high ROI benefits to using your data the right way. But adopting a strategic approach is the only way to reap those benefits, which means cutting through all of the noise to get to the heart, not of “Big Data’s” potential, but of your data’s potential.

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