Data Analytics Terminology Explained

You might have heard of various terms such as Data Analytics, Business Analytics, Big Data Analytics and Data Science. Do they all differ that much from one another? Well not correct exactly, as the purpose served are mostly similar. How do they stand out from one another?

Data Analytics, in a simple term, is the analysis of data. The purpose of understanding the data allows the analyst to obtain hidden patterns, associations or knowledge from these data’s, be it huge or small in quantity.

Business Analytics is similar to Data Analytics in a sense, but its applications are most suited for business needs. For example, to understand the sequence of items being purchased by a customer of a store which then allows the store owner to run promotions based on the results obtained by the analyst.

Big Data Analytics, by nature, serves the same purpose as Data Analytics but the term “Big” emphasises the number of records, in millions or even trillions! Compared to standard Data Analytics, this type of Analytics would usually require an immense amount of computing power or memory to hold the data. For example, the analysis of data captured by a satellite to predict and identify weather patterns.

Data Science is a discipline that includes the knowledge of statistics, mathematics and computer programming…