Data Analytics is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. There are four main types of Data Analytics that build upon one another, they are Descriptive, Diagnostic, Predictive, and Prescriptive Analytics.
Descriptive
This is the first stage of Analytics, it’s focused on the examination of data, to answer the question “What happened?” or “What is happening?”. The results are usually presented visually using pie charts, bar charts, line graphs, tables, or generated narratives. This step is the foundation but has to be built upon to access the full value of Data.
Diagnostic
This stage is focused on the question “Why did this happen?”, it’s about uncovering causality and relationships.
Predictive
This stage utilizes statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. This phase is focused on answering the question, “What is likely to happen in the future?”
Prescriptive
This is the final phase of Analytics and it uses the prior steps and decision-making techniques to examine the data and goals to determine “What should be done?” or “What can we do to meet our objectives?”
In summary:
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Descriptive Analytics focuses on “What happened”
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Diagnostic Analytics focuses on “Why did it happen?”
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Predictive Analytics focuses on “What will happen?”
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Prescriptive Analytics focused on “What should we do?”
Each phase provides deeper Insights from your Data and more ammunition to solve problems and uncover Value. Just remember no matter the tools you use, the methodologies you implement always start with business understanding/problem framing.
