Data analytics initiatives can fecilitates businesses to increment revenues, improve operational outputs , optimize marketing strategy and customer service efforts, respond quickly to emerging market analytics and gain advantage over rivals, all with the goal of bolstering business performance. Depending on the respective application, the data analyzed can have either historical records or recent trends that has been evaluated for real-time analytics.It can come from a combination of internal compute and external data sources.
Classification of data analytics
Data analytics methodologies consist of exploratory data analysis (EDA), whose aims is to find notions and relationships in information, and confirmatory data analysis (CDA), which can be infered to apply statistical techniques which can be used to determine whether hypotheses for a data set is either true or false. EDA is generally compared to detective work, while CDA is akin to the work of a judge or jury during a court trial — a distinction first drawn by statistician John W. Tukey in his 1977 book Exploratory Data Analysis.