“Big data” is a buzzword that has gone in and out of popularity since it was measured in megabytes. Unfortunately the immensity of its popularity in its current boom is doing some serious harm. Too many people are getting distracted by the “big” excitement and are only adding more friction to their goal of analysis.

A recent Microsoft research investigation facetiously titled ‘No one ever got fired for using Hadoop on a cluster’ found misguided Hadoop installations both at their company and at Yahoo!, processing less than 14G of data. The paper concludes by advising analysts to not go through the Hadoop hoops until your data size passes standard hard drive limits (currently around 1 Terabyte) or at least reasonable memory limits (512 GB).

When it comes to data analysis, it really isn’t just the size that matters, its how you use it. America has just come off of our most data-driven election ever, and we were given a front-row seat to the impacts of metric-based decision making. From the superhero tales of the data scientists behind the Obama campaign to the data failures of the Romney campaign’s final hours, and the buzz around a New York Times blogger and statistician who used visualization to predict electoral results state-by-state, data visualization and exploration was used to make decisions. Together, we watched the successes and failures of those decisions play out in the market. These datasets were sufficient for the analysis but certainly weren’t ‘big’. In fact they would probably fit in the memory of your laptop.

When Ticketbis, the international ticketing company, started to see their data with Chartio they found patterns in how and where their customers purchased tickets to concerts, sporting events and the theatre. They discovered a massive amount of purchases were made from outside the country of an event, and in response Ticketbis was able to address this substantial customer need and expand into new markets. To gain these insights they didn’t need to fill ten hard drives with data or setup any kind of mapreduce functionality. They just needed a low friction way to visualize and investigate the data they already had.

From an IBM study of more than 1,700 Chief Marketing Officers, 71% say they are under-prepared to deal with the ‘data explosion’ they face in the marketing arena, even as 79% say that customer analytics influence their strategy decisions. Sadly many of those companies will be lead astray in their solution search by the buzz, and become convinced that they have a ‘big data’ problem regardless of the size of their datasets. In the end, the companies that understand their realistic needs, and keep a pragmatic focus on the actual analysis and visualization of their data will prevail. Those companies will have the least amount of friction in finding insights into their company.

“Big data” is an impressive buzzword, but don’t get caught up in that. Let’s leave it to the journalists, researchers and marketing departments to tell us what the big data market is. Instead, focus on understanding your data. Your data is much more powerful than big data; in fact, it’s the only data you truly care about. And no matter its size or scale or scope, the principles and processes to extract meaning and information from it are often straightforward. For our part, we provide a simple interface to securely connect with the world’s most popular databases, so customers can build charts and dashboards quickly and iteratively, as an individual analyst or an entire team. Those steps — rendering your data in a visual form in a timely and repeatable fashion — are all you need to dig into your business and start asking the real questions that might change the way you do things. No one will understand that better than you, and the only data you should worry about is your data.

Dave Fowler is the founder of Chartio, the best interface for data. A Forbe’s 30 under 30 in Technology for 2011, Dave moved to the Bay Area two years ago where he joined Y Combinator and pursued his startup idea of giving a face to data. During and after school Dave did 2 years at IBM where he worked on the processor for the Xbox 360 and filed 10 patents. In school he studied Physics, two other undergrads and finished with a masters degree in Electrical Engineering.