Analytics is the art of exploring data/information with the objective of gleaning actionable insight that supports business decisions.
The term, big data, is used to define a set of data that is so massive that traditional software and database techniques are unable to process it effectively. The term, however, has been seen as very vague (7 Definitions of Big Data You Should Know About) and a number of descriptions have been used to give it a more precise and understandable meaning.
Big Data Defined
Doug Laney of Gartner originally used three main terms to define what big data is about: velocity, volume and variety. For obvious reasons, volume plays a big role in defining anything as big data. Basically, anything with a volume so huge that it cannot be easily handled by conventional means already falls under that category. Velocity then comes as a necessity, since a higher volume would require faster speeds to accommodate it. Variety also becomes a consideration, considering the different types of unstructured data that make up the volume.
Other terms have been seen as essential in considering anything as big data. Value, visibility and validity, among others, have been seen as essential in classifying anything as big data. The concept of big data also extends to the different types of technology with the ability to handle such data. These would include the different processes and tools that any business or organization would need to categorize, sort and store all these.
Big Data and Business Analytics
Because of the relationship between the two, big data has often been confused and interchanged with analytics. Basically, analytics is a process that transforms data into a set of insights that can be used to make sound business decisions. Because this involves processing and analyzing huge volumes of data, some wonder if analytics and big data (when thinking in terms of technology) can be one and the same.
When it comes to this, experts would always go back to the basic definition of the term. Volume, velocity and variety are the main attributes that distinguish big data from business analytics. Huge as the data involved in business analytics may seem, it is still a far cry when compared to how massive big data is not only in these three aspects, but a number of others as well.
Analytics is embraced in most companies for making big decisions. This is enhanced by the growth of big data and the technological advancements required to enhance its potential.