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A Clear Guide To Types Of Data Analytics
As the world is rapidly moving towards digital transformation, data has become an integral part of our day-to-day life. Analyzing this data helps towards enhancing the productivity & business gain of any organization. This is where Data Analytics comes into the play & has become the major hot topic of the present age.
What Exactly Do You Mean By Data Analytics?
At one side where Data Analytics has become a major trend however on the other hand most of the executives aren’t aware that there are different categories for different purposes. Development of any company greatly relies upon the extent of the use of right type of Data Analytics procedure based on the particular stage of development.
Let’s have a clear look at the different types of Data Analytics procedures that are extensively used by the industries today.
Types Of Data Analytics:
Predictive Data Analytics
This is the most extensively used model in the process of data analytics.
Predictive Data Analytics is used for the purpose of identifying trends, correlations & causation. It is further divided into two different types namely Predictive Modeling & statistical modeling. Both these functions work in correlation to each other.
Prescriptive Data Analytics
This is a well advanced format of Data Analytics where both AI and Big Data meet to help predict outcomes. Prescriptive Data Analytics can further be broken down into two types namely Optimization and Random Testing. This function helps for testing the right variables and it even helps in suggesting new variables which presents higher possibility of reaching to more positive outcomes.
Diagnostic Data Analytics
It can simply be interpreted as the process of examining data so as to get a better understanding of the cause and event, or why something happened. Techniques like drill-down, data discovery, data mining, and correlations are often employed in this format of Data Analytics.
It is primary aspect of reporting & the most widely used BI tools and dashboards couldn’t be possible without Descriptive Analytics. It is also divided into two different categories namely ad hoc reporting and canned reports.
As more and more number companies are adopting Data Analytics there is a spectacular rise in the demand for the qualified Data Scientists.
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