Is "big data" relevant to small and medium-sized businesses?

People are asking a lot of questions about Big Data and whether it is relevant for small and medium-sized businesses (SMBs). It also seems that various organizations define it very differently. When you hear someone use the term Big Data, instinctively you think it refers to a large volume of data, and you naturally classify it as a large enterprise initiative, but this is not necessarily the case. Big Data is as relevant for SMBs as it is for large enterprises.

It is always interesting to read about how various industry experts define Big Data. The most meaningful description I’ve come across is from the website Smart Data Collective, which says that big data refers to our ability to collect and analyze the vast amounts of data we are now generating in the world.

Specifically, I like the 4 V’s they use to characterize big data:

• Volume—the vast amounts of data generated every second
• Velocity—the speed at which new data is generated and moves around (credit card fraud detection is a good example, where millions of transactions are checked for unusual patterns in almost real time)
• Variety—the increasingly different types of data (from financial data to social media feeds, from photos to sensor data, from video capture to voice recordings)
• Veracity—the messiness of the data (just think of Twitter posts with hashtags, abbreviations, typos, and colloquial speech)

It is by no means a trivial exercise to bring all this disparate data together into a form that can be interpreted effectively, particularly for SMBs, as they traditionally don’t have the resources and capabilities to collect, model, and manage this for their own benefit. So where does this leave SMBs, and how is Big Data relevant to them?

Many SMBs haven’t implemented decent Business Intelligence initiatives on their internal data. This is changing rapidly as they realize how important Business Intelligence is to their ability to compete. Significant value can be gained by taking this first step and using it to improve the business prior to tackling the challenges associated with Big Data. The hype around Big Data naturally causes destructive interference for companies that have not gotten to first base yet, and so it becomes tempting to try to do everything at once to get that competitive edge.

My advice for SMBs starting out on the Big Data journey would be to choose one or two initiatives that will have the biggest impact in the shortest space of time and get that done as a way of initiating a Big Data project. There is no question that if implemented effectively, Big Data projects can add massive value. However, this is not a trivial exercise, especially for smaller companies that don’t have in-house infrastructure and expertise. In situations like this it may be better to outsource these projects to the experts.

An important consideration for SMBs is to leverage software as a service (SaaS) applications that may provide access to Big Data projects that serve a particular niche or industry; these should easily complement their in-house initiatives. There are many data companies that offer these types of services. A typical example of this would be a Big Data project that tracks cell phone movement in order to establish commuter patterns. An SMB typically would not have the infrastructure or expertise to do this but could benefit significantly from the output models to drive better decision making. After all, the true value of Big Data comes from being able to interpret it and then make clever decisions that will ultimately benefit the company financially.

About the author

Charles Teversham is the managing director of Sage Alchemex, the maker of Sage Intelligence