Data Cleaning and Preparation: Data can be messy and unstructured, and cleaning and preparing the data for analysis is a critical step. This involves removing duplicates, handling missing values, and transforming data to the required format.
Statistical Analysis: Understanding statistical concepts such as regression, correlation, and hypothesis testing will be done for data analytics.
Data Visualization and Reporting: Communicating insights and trends effectively used for creating reports and visualizations. Proficient in using tools such as Power BI, or Excel.