When it comes to buzzwords, Big Data is currently at the top of the technology heap. You may have your own definition, but Michael Minelli, Michele Chambers and Ambiga Dhiraj, the authors of Big Data, Big Analytics, describe it this way:
Big Data goes beyond the traditional limits of data along three dimensions: volume, variety and velocity. The combination of these three dimensions makes the data more complex to ingest, process and visualize.
It’s the wide variety of available data that really piques their interest and leads them to insights that will be useful for C-level executives as well as IT managers. Petabytes of unstructured Internet data, primary research, secondary research, location data, image data and device data is all readily at hand — and it’s vastly underutilized.
“There’s a lot of money to be made for smart individuals and companies that can mine unstructured data successfully,” the authors contend. “We are no longer limited to the structured transactional world that has been the domain of corporate information technology for the last 55 years.”
Even more interesting is the fact that because we have time and location data flooding in, “We won’t just be analyzing what we did, we’ll be analyzing what is happening in the world around us, with all of the richness and detail of the original sensation.”
Four Big Trends
Big Data analytics have come to fruition at this particular moment, the authors say, because of four ongoing trends: Moore’s Law (which basically says that technology, including storage, always gets cheaper), mobile computing, social networking and cloud computing. On top of that, traditional data management and analytics software and hardware technologies, open-source technology and commodity hardware are merging. We’re at the point where companies don’t have to toss out old data to make room for new data. They can easily keep it all and mine it as needed far into the future.
And who will do that mining? Newly minted data scientists who are showing up at this unique moment with the needed mix of math, technology and business skills. It’s these experts who will uncover the hidden value in all that unstructured data. The authors quote one study that says analytics pays back $10.66 for every dollar invested.
There’s also a huge ROI potential for cloud-based Big Data analytics now that cloud technologies are more robust. “Market economics are demanding that capital-intensive infrastructure costs disappear, and business challenges are forcing clients to consider newer models.” In other words, before you build another server room, see what you can do in the cloud.
The authors make a convincing case for Big Data analytics as a true leap forward and a real opportunity to improve efficiency, productivity, revenue and profitability. As they put it, “Comparing traditional analytics to Big Data analytics is like comparing a horse-drawn cart to a tractor-trailer rig. The differences in speed, scale and complexity are tremendous.”
It’s time to get to work.
Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today’s Businesses, by Michael Minelli, Michelle Chambers and Ambiga Dhiraj. Hardcover: 187 pages. Publisher: Wiley.