I run a small software business, what do I do with Big Data?
It’s a buzz word that has spread across seemingly every industry, from healthcare to media analytics to education. Not only are leaders across industries still trying to wrap their heads around this concept, it seems like everyone is tripping over their competition to have “the most” — and the most advanced — big data first.
But as a recent Quartz article points out,”Big data has become a synonym for ‘data analysis,’ which is confusing and counter-productive.” We’ve needed to analyze the data we have since the beginning of humans organizing and operating businesses among groups. But that does not mean, suddenly, that everyone needs to “have” big data, nor that they need all the tools and resources to make sense of that much data.
So it is important to remain healthily skeptical about the value of big data to your small business. In the words of Christopher Mims for Quartz:
Even web giants like Facebook and Yahoo generally aren’t dealing with big data, and the application of Google-style tools is inappropriate.
A recent research study published by Microsoft finds that many of the problems solved by engineers at even relatively large firms don’t need to be run on the kinds of server clusters that are the basis of much big data interpretation. Small businesses, right now, will rarely have enough data to strain even a Google Docs-powered data analysis.
That is not to say the data you do have is not important. It’s exactly the opposite. It’s too important to muddle it up by using tools that are actually ineffective for what you are dealing with. Which is why it’s crucial to tread carefully in the fanfare surrounding big data. Considering all the options and investing in the best business intelligence tool is the most important thing you can do for your business data.
It is important to understand the potential benefits and shortcomings of big data. How much value will it yield, compared to its cost and larger infrastructure?
In the realm of data analysis, even among people and tools that are as optimized as possible, more data also means the risk of more false positives. In some cases, big data is as likely to confuse as it is to enlighten. Big data is a deep pool containing a number of complex disciplines: statistics, data quality, algorithmic science and programming, to name a few.
Which is why sound research and consideration of all your data management tools is the best thing you can do for your data, whether it’s big or small or in between. Don’t let buzz words cloud your decision-making. You don’t need huge amounts of data that exist arbitrarily; you need the right data, and you need to work for you.