5 Important Analysis Techniques for Data Scientists for Quantitative Analytics
5 Types of Analytics and Their Meaning With Usage
Analysis and steps involved in analysis are very important to reach to the right conclusion. It will help to derive meaning out of raw data which most of the world is striving for. This brings us to the discussion of different types of analysis and their respective importance in data analytics. To be frank, knowing them will give depth of understanding to utilize the same in actual environment and have edge over others.
Descriptive Analytics
This is the first stage in the business analytics in the modern day. This stage will give quite a good analysis about the raw data. It is considered time intensive and important to get the first level understanding of data.
This will go through the historical data and helps in analyzing existing patterns/trends as an information.
Finds answers to the questions which is already occured.
In simple, it scans through the past data, understands historical data and mines out the patterns from that. It could be termed as post mortem analysis and very effective for management reporting. Use cases are clustering, finding the relationship i.e, association rules and summary statistics…
