<img src="https://certify.alexametrics.com/atrk.gif?account=YiINr1zDGU20kU" style="display:none" height="1" width="1" alt="">

AcctTwo Blog

Is Big Data a Bust?

Big Data has made a big impact, but it hasn't always been positive.If you roll your eyes a little when you hear the phrase "Big Data," you're hardly alone. For around a decade now we have heard endlessly about the vast potential of a data-driven future. And everything from restaurant service to automotive safety was supposed to improve once analytics were applied. The key to unlocking anything and everything was promised. Unfortunately, it hasn't arrived yet.

Most companies large and small are still struggling with the same problems they have for decades. Only now they are struggling to corral huge data sets and extract obscure insights as well. Big Data has made a big impact, but it hasn't always been positive. This piece will try to answer why.

Big Data is Not What is Valuable

The problem is not that data is worthless or meaningless. Just the opposite is true, especially as the scale grows. The problem is that too many big data initiatives have focused on the data itself and not on when, where, why, and how, to find actionable insights within it.

Companies eager to embrace analytics have begun collecting as much data as possible and pooling it as quickly as they can. But in their enthusiasm, they have not prioritized accurate data, up-to-date data, complete data, or relevant data. And as a result, their efforts at analytics have been cumbersome, contradictory, and questionable.

Decision makers must realize that big data is simply a means to an end. The ultimate goal is to produce forecasts and track trends that have a direct bearing on future fortunes. That way strategy is based on empirical insights and objective evaluations. This confidence is far more valuable than the data itself.

What Big Data Needs to Work

Big data strategies are still evolving. But there has been enough trial and error at this point to suggest some surefire strategies for success. Rely on this two-pronged approach to avoid common big data pitfalls.

  • Collect More Quality Data – The value of your insights and the volume of your data are directly proportional. The larger and more varied your data set is the better, but don't sacrifice quality for quantity. If you are going to avoid consequential errors and catastrophic omissions, you must rely on good data.
  • Use the Right Tools and Services – Locating actual insights is much easier to do with tools that automate the search process and give the user flexible levels of control. That way they spend less time searching around and more time applying what they learn. This same goal can be achieved by outsourcing analytics. Experts deal with the data and deliver insights on demand.

The key to making any big data initiative work is honesty. Companies must understand what they are actually capable of and what they need to bring those capabilities up to speed. AcctTwo can help you bridge the gap in whatever way works for your company. Contact our experts to start the conversation.

Topics: Business Intelligence / Analytics Big Data