Growing Pattern of Analytics in Business

You must have heard of god, place, people, machinery,Organizations and even celebrities getting worshipped but ever heard of software and applications getting worshipped? I bet not. There was a time when Microsoft Excel was worshipped by individuals, school, colleges and even organizations; be it small or big. When the giant worksheet used to pop up in front of anybody either amateur or professional, its supremacy was enough to agitate anybody sitting in front of it. This was the case even for a professional who handled it for many years. Name the data related tasks you want to execute on excel, and it gives results more than expected. That’s why many industries,Organizations brought this application into their toolkit for data handling and analysis for the same. For more than two decades after its launch, there was sovereignty of this application everywhere.

With time, things and industry changed a lot. Software developers have now given industries ample of data handling and analytical tools that the stature of Microsoft Excel has contracted in the business because now analytics is not about calculating probability, average and plotting the graphs. In business, analytics has more to contribute than generating teeny-weeny numbers and reports.

In business, analytics refer to the practices of continuous study, exploration and investigation of past performances to create a vision for future decisions to scale up the size of business through databases. Just like the human beings, ‘Analytics’ also has its own evolution story in terms of business. It began in the 1970’s when the Relational Databases were invented by Edgar F. Codd, which allowed users to do tasks in Sequel and retrieve data from their database. In the late 1980s, the amount of data which was being collected continued to grow and the inflow of it was at its peak. During this time, the layout of Data Warehouses was developed to store the inflowing data on hard-disks and cloud both to transform it into decision-making support systems. In 1989, Business Intelligence was adapted by the industry to get support in making better business decisions through exploring, collecting, and analyzing the assembled data stored by an organization.

The 90s witnessed the process of fetching patterns within hefty data sets through another new concept of Data Mining. These unorthodox practices of analyzing the data provided results that were both eye-catching and favorable. The idea of Data Mining came into existence directly from the concept of Database and Data Warehouse technologies.  In 2005, the notion of Big Data was brought by Roger Magoulas and why so? It was so because for Business Intelligence Technology it was getting impossible to cope with the large amount of data. Software like Hadoop, Apache Spark and Apache Cassandra came to process the Big Data. Now you must be thinking that hey? It’s been so long, where are some facts about Microsoft excel? Well, with the introduction of Big Data, it was that year from where the significance of Microsoft Excel started dwindling with the speed of a snail.

After the introduction of Big Data, the rise of four types of analytics was witnessed: Descriptive, Diagnostic, Predictive and Prescriptive Analytics. Descriptive Analytics summarizes the existing data, Diagnostic Analytics focuses on past performance, Predictive Analytics forecasts the possible outcomes and Prescriptive Analytics recommends more than one modus operandi.

Business analytics answers anything when an industry raises a doubt from what is happening in an industry to what are the possible solutions to rubber-stamp for growing the business further. It has helped in making rational decisions instead of a ‘going with the gut’ approach.