Data Science Series: Data Analytics what is it and types

 Data analytics is concerned with examining, transforming and arranging data so that you can study it and extract useful information. There are five types of data analytics:-

1. Descriptive Analytics - Helps you answer questions about what has happened based on historical data Eg generating reports to view organizations sale and financial data.

2. Diagnostics Analytics- Helps you answer questions why things happened. They supplement descriptive analytics. Take findings from descriptive analytics and dig deeper to find cause. Three steps

a. Identify anamolies in data 

b. Collect data related to anamolies

c. Use statistical technologies to discover relationships and trends to explain these anamolies

3. Predictive Analytics- Help answer questions what will happen in future. Use historical data to identify trends and determine if they are likely to re-occur. Include statistical and ML techniques such as Neural networks, decision trees, regression.

4. Prescriptive Analytics - Help answer questions what decisions should be taken to achieve a goal or a target. By using insights from predictive analytics data-driven decisions can be made. Allows businesses to make informed decisions in face of uncertainty. Use ML strategies to find patterns in large datasets. BY analyzing past decisions, events, likelihood of different outcomes can be estimated.

5. Cognitive Analytics- Draw inferences from existing data and patterns, derive conclusions from existing KB, then add these findings back into KB for future inferences - a self learning feedback loop. Help you to learn what might happen if circumstances change and how you might handle these situations.