Last week I wrote about the benefits and disadvantages of “data lakes,” huge repositories of different data types stored in raw form that are easily accessible to employees for analysis. Data lakes provide a method for enterprises to managed their big data in a cost-effective and efficient way.
Many enterprises, however, struggle to manage the data flooding their networks and systems from the Internet, mobile devices and apps, social media and the Internet of Things. Never mind a data lake; these enterprises feel like they’re floating in an ocean of data.
The thing is, most of that data pouring into enterprises isn’t strategically useful. Yet enterprises will continue to spend a lot of money simply collecting and storing all of this data. Is there a way around this dilemma?
Forbes contributor and big data author Bernard Marr thinks so. He writes:
If companies and individuals want to avoid drowning in data while thirsting for insights, they have to develop a smart data strategy that focuses on the few things they really need.
Rather than worrying about “big data,” companies would do well to instead focus on Smart Data — in other words, defining the questions they need answered, and then collecting and analyzing only that data which will serve them in answering the question.
Marr is right on with his point. Returning to the ocean analogy, smart fishermen don’t drag nets around every square inch of the sea; rather, they go to where they think they’ll find the most fish. In other words, they formulate an intelligent strategy and act upon it.
“Without a smart plan of action to use the data to produce business insights, the data itself becomes a white elephant — expensive and useless,” Marr concludes.
Does your enterprise have a smart data strategy? Or is it lost in a sea of big data?