4 Types of Data Analytics Explained in Marketing Language
This article will discuss the 4 Types of Data Analytics, or the 4 steps in Data Analytics, in a marketing-friendly manner for marketers, managers, or business owners to understand the guidelines and methods to communicate with the Data team. Understanding what you need and what the Data team is doing is crucial in working with data.
What is Data Analytics?
Data Analytics is the process of turning various data, not just analyzed or summarized into reports ready to read. This is because it is only the final step in Data Analytics. It’s like going to a restaurant and ordering a plate of basil fried rice and summarizing it yourself, thinking that cooking is just ordering and eating. In reality, Data Analytics involves many steps, starting from managing the ready-to-use data, gathering data from various sources, creating models, doing data visualization, and finally summarizing what new insights we have gained from Data Analytics.
4 Types of Data Analytics consist of four main steps:- Descriptive Analytics: Analyzing to understand what has happened.
- Diagnostic Analytics: Analyzing to understand why something happened.
- Predictive Analytics: Forecasting what might happen next.
- Prescriptive Analytics: Determining what will happen if we take a particular action.
While steps 1 and 2 analyze data to understand the present or past, steps 3 and 4 focus on forecasting the future, often building on the results of steps 1 and 2. Let’s take a look at examples of how to apply these 4 steps in Data Analytics in a marketing context.
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