Data analytics is the process of examining data sets to uncover hidden patterns, correlations, trends, customer preferences and other useful information that can help organizations make smarter, more informed business decisions. The three types of data analytics are:
Descriptive Data Analytics
Descriptive data analytics is putting in live data. For example, if you wanted to know how the sales numbers from the beginning to the end of the year, the descriptive data is set out and from that, you can use it to spot trends and see what you can do to improve and what’s working where.
Diagnostic Data Analytics
Diagnostic data analytics shows why it is happening. If the sales are down and you want to know why the diagnostic data will allow you to find the root cause of the problem.
Predictive Data Analytics
Predictive data analytics looks more into the future. Forecasting, trend lines, and other tools can be used to see how the numbers will go up or down (sales) over a certain time period.
Prescriptive Data Analytics
As the same sort of suggests, prescriptive data analysis is what is used to start finding solutions to problems to get the outcomes initially intended for the business.
This is just a brief introduction, hence why it is so short, but I will following up on this in more depth in the future 💯.