Big Data is everywhere. Everyone knows it, everyone is talking about it. But what exactly is Big Data?
“How big, really, is Big Data? This is actually a very intriguing question whose answer seems to lack consensus at the moment but whose ambiguity has not stopped the use of the term. A common misconception, however, is that big data refers solely to the size of the data: if it is data and it is big then it must be big data. While size is certainly an element of the equation, there are other aspects or properties of big data not necessarily associated with size.”
In this video, we learn interesting facts about Big Data, how it is being generated and at which pace. It also discusses misconceptions about it and provides a clear definition of Big Data. Below are some conclusions from the video:
- Big Data is any attribute that challenges contraints of a system capability or business need.
- Big Data refers to the sheer volume of data to be analyzed within a given time frame or within a geographical boundary.
- Not all Big Data are the same from a structure perspective: some Big Data have its format well defined like transactions in a database, some Big Data may be only a collection of Blog entries that contain text, tables, images and video all kept in the same data storage.
Despite of the size, speed or source of the data, Big Data drives the need to make sense out of the chaos, Big Data drives the need to find meaning on the data that is constantly changing and to find relationships between the data created. Understanding this interconnectedness and being able to harvest the information hidden in Big Data unlocks Big Data’s value which can only be gained by being able to tackle our own Big Data challenges.
Collecting, analyzing and understanding Big Data is becoming a differentiated strategy today but it will become a fact of life tomorrow. Running analyses at the finest granularities while you still have enough data for the results to be meaningful and accurate leads to more precise action and in turn more profits and savings for the company and customers. So when it comes to big data the question is not “Why should I care about Big Data?” but “How can I get closer to Big Data and how can I start taking advantage of it now?