Quality assurance for data analytics

Abstract

Quality Assurance is a technique for ensuring the overall software quality suggested by Global Standards bodies like IEEE. The Quality Assurance for Data Analytics requires more time and a very different set of skills because Software Products, which are used for Data Analytics, are different than that of traditional ones. In result, these Software Products require more complex algorithms to operate and then for ensuring their quality, one needs more advanced techniques for handling these Software Products. According to our survey, Data Analytical Software Products require more work because of their more complex nature. One of the possible reasons can be the volume and variety of Data. On the same hand, this research emphasizes on testing of Data Analytical Software Products which have many issues because testing of these Software Products requires real data. However, every time the testing of these Software Products is based either on dummy data or simulations and these Software Products fail when they work in real time. For making these Software Products work well before and after deployment, we have to define certain Quality standards. In this way, we can get better result producing analytics Software Products for better results.