“Information is the oil of the 21st century, and analytics is the combustion engine”- Peter Sondergaard, Senior Vice President, Gartner
Big Data and Business Intelligence are becoming an increasingly important source of statistical information which is used as a vital part of the critical decision-making process of all businesses. Bernard Marr, in his article titled “4 Ways Big Data Will Change Every Business” reiterates the industry-belief that “big data and its implications will affect every single business -from Fortune 500 enterprises to mom and pop companies – and change how we do business, inside and out.”
Today all decisions in an organization are being made on the data available to them. Hence it has become critical to ensure that the does is free of any issues or defects. The way to ensure that there are no data issues and it is fit for the business, is to test, validate and compare it regularly.
Some of these organizations are either testing the data manually or not testing at all. We all are aware of the issues and challenges of testing anything manually but data testing has its own set of unique challenges on top of that. Below are some of the data testing challenges every organization encounters. The challenges mentioned below are for data testing which translates into Big Data Testing, ETL Testing, Data Migration Testing and few others.
