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  • 4 Different Types of Data Analytics - An Overview

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    Data analytics is becoming very on-trend. It is in such demand that a great number of people are becoming interested in learning more about it. A job that is promising, rewarding and comfortable is what is attracting the youth towards it. Online courses are offered by many institutions in the field of data analysis. The field is considered to be quite vast and so it is necessary to understand different types of analysis.


    This article discusses the various types of data analytics that exist as of today. Read below to understand which type may suit you best and to decide accordingly.


    1. Descriptive Analysis:

    This is a type of analysis that explains the how of a problem. It describes everything that has happened over a period of time. For Example: A manufacturing unit collected data regarding the operation of its machines for a year, descriptive analysis, then assisted the management team in preparing the information in such a way that it then told them the number of times the machines were run, the amount of output that was generated and the time intervals for their operation.


    2. Diagnostic Analysis:

    This type of analysis lays emphasis on defining the reasons behind an event that has occurred. It goes a step beyond descriptive analysis. For Example: In the same situation noted above, diagnostic analysis would lay emphasis on telling the management team why a machine broke down or how many machines were working at their full capacity. This would provide the output from all machines in the manufacturing unit which would define which specific machines were leading to any inefficiency.


    3. Predictive Analytics:

    Such an analysis tries to create hypothetical situations to present possible reasons for a problem that might have occurred or for the current situation. Such an analysis makes assumptions about a current situation and then attempts to predict the future. For Example: based on the current records of the machine operations of a business, the predictive analysis can make a conclusion that the production would increase over time to economies of scale. This information is extracted with the help of trend analysis.


    4. Prescriptive Analytics:

    This is a cautionary type of data analytics. It suggests various ways in which a company can operate to ensure they are working at a safe level without being affected by external factors. For example: If in the problem noted above, the analysis draws conclusions that machines are getting older and could lead to unsafe working conditions for the employees, then the analysis would recommend that new machines be installed.



    It is not mandatory that an analysis needs to be carried out in isolation. A combination of analysis is also done by the analysts. Such analysis needs to have a problem statement defined. Therefore, an analyst needs to know all the different types of analysis to perform them effectively. Many institutions help students get trained in this field.


    About the Author

    The author is a content strategist at ExcelR, a company that has been dedicated helping students who want to learn data science and enroll in data analytics certification courses. 

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