Data Analytics in is of four types. Each type of Data analytics uses different skillsets to achieve the desired outcome. Different skillsets are required to learn these concepts; choose your path to upskill strategically based on your interests.
1. Descriptive Analytics - What happened in the past.
It is just reviewing the available information and reading the outcomes of the data. The skillset required for this stream of analytics includes Excel, PowerPoint, and storytelling.
2. Diagnostic Analysis - Why this happened.
It means diagnosing the outcome using the given information, drilling down into the data core to identify the root cause for the actions. SQL is one of the top desired skills in diagnostic analysis, along with Excel and storytelling.
3. Predictive Analysis - What is likely to happen in the future.
This is the most exciting part of data analysis. It involves the usage of various statistical techniques for data analysis and building models to predict the outcome using the given data. It includes machine learning techniques to predict actions and results. The skillsets include Python, machine learning, and statistics.
4. Prescriptive Analysis - Optimization for enhanced results.
Once you build the model, it's not over; it's a continuous iteration to find the best possible model fit that produces the most accurate results and develop strategies to optimize business solutions.
Each type of Data Analytics demands a unique set of skills. Choosing your path allows you to cultivate expertise in line with your interests.