SQL - SQL is the database coding language that extracts, organizes, and manages large datasets stored in relational databases.
Statistical programming language - Statistical programming languages like Python and R can help you perform analysis in a way no spreadsheet can do.
Microsoft Excel - Microsoft Excel is one of the most well-known tools for working with data. Apart from providing quick analytics, it offers an easy way to store data.
Machine learning - Machine learning is a branch of Artificial Intelligence (AI) that is important in data analytics.
Mathematical skills - Data analysts often need to quantify and process loads of data. Because of this, they should possess strong mathematical skills.
Data visualization - Data visualization is the ability to communicate and present your insights and findings via graphs, charts, or other illustrations.
Data collection and cleaning - Data collection is the process of collecting and managing data based on the variables related to the goal an organization wants to accomplish through analysis.
Problem-solving - Many organizations hire data analysts to interpret and analyze data to solve or prevent problems from occurring.
Communication skills - Data analysts work together with diverse departments and professionals to develop profitable solutions for an organization.