Confirmatory Data Analytics
The Confirmatory Data Analytics deals with the already existing methods, theories or hypotheses. The major objective of confirmatory data analysts is to prove the pre-existing theses, models or theories either true or false. These analytics are heavily relying on probability models and must be open to all the untested assumptions. The outcomes of such analytics are a specific answer to the specific question.
Advantage
- These analytics provide precise information under similar circumstances.
- The methods and theories are well established.
Disadvantage
- Since it is based on assumption under similar condition, when condition changes the results also gets changed.
- It is difficult to track the changes in case of unpredicted outcome.
Exploratory Data Analytics
The Exploratory Data Analytics deals with the new features of data to discover and implement new methods, theories or hypotheses. The major objective of exploratory data analysts is to introduce new models, theories or hypotheses. In this the data analyst doesn’t require any assumption. These are based on data calculations without any preconceptions. In actual the exploratory data-analytics tries to remove the assumptions from confirmatory data analytics technique. These are heavily relying on graphical representation (or display) of data.
Advantage
- This technique results in more realistic data.
- The level of accuracy attained in this technique is very high.
- It results in a very deeper understanding of processes.
Disadvantage
- Most of the time, it lags in definitive answer.
- Require high level of accuracy and judgment.
Qualitative Data Analytics
The data analysis from non numeric forms like images, videos, audios, documents, notes or interview are comes under Qualitative Data Analytics. Qualitative Data-Analytics usually require involvement of peoples or organizations and their symbols, activities, sign etc they imbue with meaning. The major objective of Qualitative data analytics is to create understanding or result in some form interpretation from the data collected.
Now days the term “DATA ANALYTICS” is widely associate with “Business Intelligence”. This term is use to define or associate with everything used in business intelligence from OLAP to Dashboards to CRM analytics to Real-Time analytics to Dynamic Analytics.
