Its stage of development determines the optimal sort of data analytics for a business. Most businesses are probably currently employing analytics, but it often only provides insights to make reactive, rather than proactive, business decisions. The post graduation in data analytics has a wide scope in today’s day and age.

Four Primary Forms of Data Analytics

1. Data analytics for prediction

Predictive analytics is possibly the most widely used type of data analytics. Predictive analytics is used by businesses to discover trends, correlations, and causality. The category is further subdivided into predictive and statistical modeling; nevertheless, it is vital to note that the two work in tandem.

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2. Data analytics that is prescriptive

Prescriptive analytics uses AI and big data to forecast outcomes and determine what actions to take. This type of analytics is further subdivided into optimization and random testing. Prescriptive analytics can assist answer questions like “What if we attempt this?” and “What is the optimal action?” by leveraging advances in machine learning. You can test the correct factors and even propose new variables that have a better possibility of producing a positive result.

3. Data analytics for diagnostics

While not as thrilling as forecasting the future, evaluating data from the past can be helpful in steering your organization. Considering data to determine the cause and event or why something happened is known as diagnostic data analytics. Drill down, data discovery, data mining, and correlations are all standard techniques.

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Diagnostic data analytics can assist in determining why something occurred. It, too, is subdivided into two subcategories: discover and alerts and query and drill-downs. To obtain more information from a report, questions and drill-downs are employed. For example, consider a sales representative who closed much fewer deals in one month. A drill-down could reveal fewer workdays as a result of a two-week vacation.


Alerts and discovery Notify of a potential problem before it arises, for as a warning about a decrease in staff hours, which could lead to a fall in closed deals. You may also employ diagnostic data analytics to “find” information like the best candidate for a new position at your organization.

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4. Analytical data that is descriptive

Descriptive analytics is the foundation of reporting; business intelligence (BI) tools and dashboards are inconceivable without them. It answers the fundamental issues of “how many, when, where, and what.”


Again, descriptive analytics can be divided into ad hoc reporting and prepared reports. A canned message has already been designed and contains information on a specific topic. A monthly report sent by your ad agency or ad team comprising performance numbers on your most recent ad campaigns is an example.


Ad hoc reports, on the other hand, are created by you and are typically not planned. They are generated when a specific business question has to be answered. These reports are handy for receiving more detailed information on a particular query. This was in brief about four types of data analytics and practices. To know more about; best machine learning course, click here.

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