SMBs Need Proper Tools to Refine Big Data

Top Predictions for Big Data in 2014

According to a recent Entrepreneur article, small businesses should find effective ways to analyze data in order to give their customers what they need without pushing too hard to gather more data from those same customers. Sounds simple, yet complex.

And when you also consider that data is increasing exponentially, and the way Big Data has been multiplying, it’s no wonder small to midsize businesses (SMBs) have become quite overwhelmed about how to collect, sort, and use Big Data in any effective manner.  

But what SMBs need to realize is that the key to using data is “refinement.” In his Entrepreneur article, Suhail Doshi explains:

Data for small businesses doesn’t always need to lead to a technological or market breakthrough. It’s mainly about refinement, using data to establish segments so marketing and sales can adjust to those segments. Data means finding the repeat loyal customers and providing them with outlets for brand building such as social media contacts or even an old-school free t-shirt. At its core, data for the small business means streamlining processes and finding what is most relevant to customers.

In the Midsize Insider, Sue Poremba further supports this theory and adds that to ensure that the data is analyzed, understood and targeted to the proper customer segment, the business must be sure to use the right tools. With Big Data, though, traditional business analytics tools just won’t cut it.

One new tool available to some SMBs for Big Data analysis is SAP’s Business One. The latest version, 9.0, runs on the HANA in-memory relational database, which allows Business One to perform analysis on large quantities of Big Data in real time. The business management solution can run in the cloud, on-premise or as a hosted service.

SAP touts that this version of Business One will cut down Big Data analysis time from days to seconds. That should help SMBs overcome their fear of Big Data so that they can create effective and efficient ways to use such data to increase their customers’ satisfaction.