The 4 types of Data Analysis and what they address
Data Analysis is the buzzword we probably won’t get over for a long time. There’s power in knowledge and answering the questions your business has, comes with its own costs.
Each type of technique delivers different insights. The resources the analysis require vary from the complexity of the type. Take a look at them below:
Descriptive Analytics – What happened?
Figure out what is going on.
This is the most common analytics in business today. It provides insights based on past information, and all that material is usually summarised in the shape of dashboards. By tracking your past and present activity, descriptive analytics signals that something might be going wrong, but doesn’t answer why.
Diagnostic Analysis – Why did this happen?
Explore in-depth insights on your problem.
This one goes a step further than just showing you a picture. So you are aware of what is going on within your business, what’s the reason behind your current state though?
Diagnostic analysis understands the correlation between your variables so you can explore the relationships they have. It examines the cause of your outcomes and past results.
Predictive Analysis – What will happen?
Forecast and predict future trends.
Envisioning an unknown outcome is at the core of this analysis. It identifies patterns in historical data and assists in understanding the future. The accuracy, however, depends highly on the quality of the data and on how stable a situation is.
Prescriptive Analysis – What should you do now?
Choose the course of action that would help you get where you want.
Through machine learning and optimisation techniques, it chooses the best option to achieve a certain outcome. You can understand the advantages of future opportunities and reduce certain risks. Because of the nature of statistical algorithms, besides historical data, prescriptive analysis requires outside information as well.
What insights are you using to help boost your enterprise?