This path is for anyone starting data analysis from scratch. It begins with spreadsheets and statistics, moves on to programming and presentation tools, and ends with big data.
Why here: Excel is the simplest place to work with tables and data before moving to larger tools.
After it you can: You will be able to build spreadsheets, use functions and formulas, and analyze data with charts and pivot tables.
Why here: After working with tables, you need to understand the statistical tests that data analysis relies on.
After it you can: You will be able to enter data in SPSS, handle missing values, and analyze data with various statistical tests.
Why here: Programming lets you handle more types of data, and more flexibly, than spreadsheets do.
After it you can: You will be able to work with different types of data in Python, create charts, and carry out data analysis projects.
Why here: After analysis comes presenting the results in clear reports and dashboards.
After it you can: You will be able to create interactive reports and dashboards in Power BI and analyze time-based and geographic data.
Why here: This course widens your data visualization skills with a tool specialized in visualizing data.
After it you can: You will be able to analyze data in Tableau, create maps and charts, and design an interactive dashboard.
Why here: It comes last because it assumes a foundation in analysis and deals with much larger data.
After it you can: You will be able to collect and analyze big data using Hadoop and tools such as Knime and Jupyter, and carry out practical projects.
