What is Data Analytics?

 

Data analytics is the science of analyzing raw data in order to gain insight and make conclusions about that information. Every data has trends and meanings which can be interpreted by Data analytics to help a business optimize its performance.

 

We can also explain data analytics as the process of examining datasets to draw conclusions about the information they contain. Data analytic techniques enable us to take raw data and uncover patterns to extract valuable insights from it.

 

Data Scientists and Analysts use data analytics techniques in their research, and businesses also use it to inform their decisions. Data analysis can help companies better understand their customers, evaluate their personalize content, create content strategies and develop products. Ultimately, businesses can use data analytics to boost business performance and improve their bottom line.

 

 

 

Types of Data Analytics – Data analytics is broken down into four basic types.

 

Descriptive analytics describes what has happened over a given period of time. Have the number of views gone up? Are sales stronger this month than last?

 

Diagnostic analytics focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?

 

Predictive analytics moves to what is likely going to happen in the near term. What happened to sales the last time we had a hot summer? How many weather models predict a hot summer this year?

 

Prescriptive analytics suggests a course of action. If the likelihood of a hot summer is measured as an average of these five weather models is above 58%, we should add an evening shift to the brewery and rent an additional tank to increase output.

 

In our next discussion, I will be going into the details of each of these items. Till then, lets have your feed back and I will be glad to respond to your feedback.