Diagnostic analytics is the second stage of the 4 stages of data analytics.
The first stage of data analytics - descriptive analytics - explains what happened.
Diagnostic analytics is a type of data analysis that focuses on gaining insight into past events to understand the underlying causes of observed outcomes. Our main question at this stage is WHY?
It is used to identify root causes of problems and develop solutions to address them before they become more serious.
Diagnostic analytics typically involves collecting and analyzing data from multiple sources to identify correlations and trends. By uncovering patterns and relationships, diagnostic analytics can help organizations anticipate future problems and make better decisions.
This type of analytics is often used in fields such as healthcare, finance, marketing, and operations to uncover hidden patterns and improve efficiency.
Building skills in diagnostic analytics is helpful for anyone but critical for those working as data analysts and business analysts.
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