The four types of Data Analytics

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Data Analytics and Data Analysis are both terms used in the Big Data context. While they are tools that help us extract meaning from Data, Analytics is also used to predict a result.

Data analytics is a broader term and includes data analysis as necessary subcomponent. Analytics defines the science behind the analysis..   –david kasik

With the right Analytics, Big Data can deliver better and deeper insights to businesses and companies.

There are four types of Analytics that help us provide value to organizations:

Descriptive Analytics:

Is the most common and typically the first analysis performed on a dataset. It is used to answer the question What happened?

Diagnostic Analytics:

It is performed to diagnose and discover the causes of a certain reaction or activity.  Answers the question Why did it happened?

Predictive Analytics

It is used in less than 1% of organizations. With the gatter of various sources of information and contextual data, it can infer future trends or patrons using current and historical data. Answers the question What will happen?

Prescriptive Analytics

It is the most valuable and less performed due to its complexity. It requires the development of prescriptive models to predict the possible consequences of a certain action based on what we want to archive. It answers the question How can we make it happen?

Data Analytics can deliver valuable information to business and help them to make more accurate decisions that lead them to the right path.

Here is a short video that introduces the four types of analytics in a easy and comprehensive way:

 

-Happy analytics!

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Sara García works as a social media data analyst at Allied Global. She has more than 5 years of experience in building backend web applications. In the near future, she plans to pursuit a master degree in data science.
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