Big data analytics provides enterprises with a range of new insights into how they should operate their businesses. While taking full advantage of this emerging practice is difficult, many organizations are using it extensively, pressuring competitors to keep pace. Understanding the technology available and how it is being used can help organizations use big data analytics to meet their own business goals.
Over the past few years, the scale, speed, and power of analytics have been dramatically transformed. The amount of data available from the internet, combined with advances in software to make use of it, has created a practice called "big data analytics." It can provide types of information that were not available in the recent past and it has the potential to do so in real time.
The advent of big data analytics has created new challenges for executives. There are new types of data to be understood and incorporated into strategic planning. Making big data analytics work is not simply a technical task but an executive strategy-setting activity. Some core business practices in certain industries could be transformed in the coming years.
The use of big data analytics is still maturing, but it is already common. Major vendors such as Cisco, Google, and IBM offer solutions and services in the market. But the many elements of the process—from gathering data to spotting patterns to translating raw findings into actionable information—are rarely provided by a single solution. Instead, enterprises must build their own systems, using an understanding of their business goals as a guiding factor.
The Evolution of Analytics
Using software to analyze data is an old practice. Analytics have been employed for purposes as diverse as predicting the weather to determining what line of business a company should enter. Starting a few years ago, the practice began undergoing what has been called a revolution. The use of the Internet has greatly expanded the volume and breadth of data available, and many diverse tools to crunch the data have been created. The difference is not simply that analytics have become better, but that they are fundamentally different. This new discipline is Big Data analytics. Describing this change as it began to fully emerge, a 2012 Harvard Business Review assessment of the development offered the following example: "Booksellers in physical stores could always track which books sold and which did not. If they had a loyalty program, they could tie some of those purchases to individual customers. And that was about it.