Data and analytics constitute two different words, wherein data refers to detailed information and analytics refers to the use of statistical and mathematical techniques to draw information. Thus, data analytics refers to the methodology pertaining to investigating raw data using many techniques, tools as well as software. It involves business intelligence to take appropriate decisions. Various MNC’s use data analytics for their decision making process. Data analysis is also used for scientific researches and findings, so as to verify various theories and models.

There are various types of data analytics, and these are described below:

  • Descriptive analytics: This technique is used in presentation of data that can be used by humans. Furthermore, descriptive analytics us used to understand how various activities might affect certain consequences. Various data mining techniques are used for descriptive analytics. Various examples of descriptive analytics include inventory, customer, market, sales report and others.
  • Predictive analytics: Probability constitutes the key to predictive analytics. This often tells us what might happen in the future. Various organizations take decisions on the basis of probability of occurrence of various events. Hence, statistical modeling technique is often used to execute the procedure of predictive analytics. Predictive analytics is often used to discover patterns to capture relationship between various factors that affect decision making.
  • Prescriptive analytics: This branch of analytics helps in prescribing various results of the future. This analytics method also uses algorithm, machine learning, business rules as well as modeling procedures to execute actions. Prescriptive analytics data could be transitional as well as historical. Presciptive analytics helps in optimization of various functions of the business, so as to bring about progress. Well developed MNCs used this technique.

Data analytics helps in breakdown of large data into smaller forms, helps in decision making process, helps in eradicating biased information, so as to verify data. It also helps in getting meaningful sense of the information. Data analytics is a rapidly growing area and constitutes of many tools and techniques to reach organizational goals. The software used for data analytics could be simple in the form of an excel sheet which could involve the use of advanced tools such as Oracle and SAS.

An MS-excel spreadsheet might look simple and it serves a variety of functionalities. This is also used as an analytical tool for many business functions. SAS is used much in the business market. It is also an autonomous vendor in the market. SAS has much capability to execute statistical analysis. The software package called Statistica supports many analytical techniques. Furthermore, statistica serves as a complete package for data mining, data analysis, data visualization as well as data management. Another important software to use is the Salford system for predictive analysis as well as data mining. This software is very accurate and allows to develop many models for various databases. Another statistical computing software is MATLAB which permits plotting of function and data, algorithm implementation as well as creation of operator interface. Various topics are covered by our experts of data analytics such as analysis of variance, regression, experimental design, correlation, sample size and much more.


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