The process of data analytics analyzes the raw data to see the trending and to find the answer of the raised queries. This defines the broader meaning of scope in that field. This analysis has many types of techniques with several goals to achieve. Saas predictive analytics is a process that has some elements with various indications. A combination of these elements will provide a well-specified data analytics, which will give a distinct view about what was done in the past, what has been done in the present and what should be done in the future. Online spss data analysis is a set of software programming for social science in a statistical manner. Many researchers in analyzing complicated statistical data’s use this. Cloud based data analytics is knowledge of the sea for machine-learning algorithms including analysis of texts, extensions of the open-source with big integrated data has and seamlessly deployed apps. Digital data analytics is the method of analysis of digital data from different websites and mobile applications providing a distinct view about the relationship with the customers and the needing areas of improvisations.
Descriptive Data Analytics is the process of data analytics that starts by providing descriptive data’s by using conventional indicators like Return on Investment (ROI), Key Performance Indicators (KPIs). Sometimes it includes the trends by summarizing the descriptive data has and excludes the direct indications. Next is to extract the data by using the advanced tools to predict and to discover the tools including the usual stats along with the machine learning, data sets and common computation power. Technologies as if sentiment analysis, neural networks and natural language processing are used which provides acuteness of data. Big data analytics helps to state the conclusion from many complicated data has to know about the success and failures for the shareholders by relevant data collection, processing and analyzing and finally visualization of data.
Diagnostic Analytics states about explanations of the queries. In this method of analysis, they collect the descriptive analysis data and go down in depth to know about the causes so that they can be analyzed for improvisation. Predictive Analysis says the answers for the prediction of the future. This takes the data from the history, finds the trends and states the condition of repetitions to predict about the future using decision trees and regression. Prescriptive Analysis uses predictive analysis to inform about the possibly needed decisions with vagueness. Various applications as well as programming languages can be used in the process of data analysis. Python, SQL, and R can be considered as the most effective programming languages that can be use in this process.