3 Ways DevOps Can Increase the Value of Organizational Data

There’s a reason the term “data mining” came into existence. Enterprises sit on a vast resource of information—millions of digital gems that, if fully extracted, can not only answer many of their toughest questions, but also help them meet their most ambitious organizational goals.

DevOps professionals have a unique opportunity to impact this mining process. Their vision can transform the way their organizations utilize data by building fresh capabilities and strategies into the applications and platforms they create. Yet, recent advancements in data science, particularly the use of parallel processing platforms that interrogate massive datasets in near-real time, are changing the game as well. 

Time-to-Insight Is Shrinking

Parallel processing improves analytics along two important paths.

First is the time requirement. When organizations are able to process billions of rows of data in milliseconds, it changes the value of that data. In many industries—financial services, for example—there is a big difference between a query that is answered in seconds or minutes, versus one that is answered in a fraction of a second. Those small deltas in time can make a big difference in the bottom line. As they say, time is money.

The other path is the curiosity factor. In conventional analytics, the paradigm is to ask a question and get an answer. But if the user can ask one question, get the answer and then ask three more questions based on that result, without concern for a time penalty, it creates an opportunity to be more curious. This is a pain point that is underappreciated and largely overlooked in most organizations. Without speed and agility, decisionmakers can end up in a rut, asking the same questions over and over again because the time/value equation never improves.

When queries only take milliseconds to answer, it’s easy to ask new questions, dig deeper into data and look at problems in entirely new ways. DevOps has the ability to leverage the potential…

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