Data analytics

Data analytics and advanced mining technologies analyse data with exploratory data analysis which is used to describe data and establish a pattern and relationship in the data with the help of statistical methods. Confirmatory data analysis evaluates data using statistical methods. Data analytics analyse the data in the manner described in Figure 2.2.

Data can be analysed in different ways depending on whether it is past or future data. Based on different types of analytical methods, data can give fruitful solutions. The analytical methods comprise following methods (Figure 2.3):

• Descriptive analytics: In this analysis, history of past data is analysed, that is how data got modified according to the process. For example, amount of rainfall occurred in various districts and other information of rainfall data are considered.
• Diagnostic analytics: In this type of analysis, the reason for problems and other special deeds according to the process are analysed. For example, analysing the causes for excessive or less rainfall at a particular location.
• Predictive analytics: This is a forecasting method, which analyses the data and predicts the future level of the process. For example, in rainfall data, the amount of rainfall will be predicted based on the history of past rainfall data.
• Prescriptive analytics: This is an analytical method, which optimizes the predictive result of the process. For example, increasing the accuracy and using optimization techniques to produce better outcomes in the rainfall data.