Self Guide to becoming a Data Analyst

1. Maths and Statistics ??

• Statistics and Probability
• Algebra and Linear Algebra
• Calculus and Discrete Mathematics

2. Excel (Basic to Intermediate) ??

• Editing text and formulas
• Excel functions and lists
• Worksheets and pivot tables
• Formatting data and data validation
• Working with charts and templates
• Lookup, macros, and VBA

3. Python Programming ?? ??

• Syntax and basics
• Data structures and Algorithms
• Pandas
• Numpy
• SciPy
• Matplotlib

4. SQL and Database ??

• DBMS, Normalisation and ERD
• SQL syntax, data types, variables, SELECT, WHERE, AND, OR, NOT
• Insert, Update, Delete, Min, Max, Count, Average, Sum
• Like, In, Between, Top, Group By, Order By, having, exists, any, all, case
• Joins such as Inner, Outer, Left, Right, Full, and Self joins
• Database-related table commands such as create, alter, update, drop
• SQL constraints such as Not Null, Unique, Check, Default, Auto-increment
• Views, triggers, functions, PL/SQL, injection, hosting

5. Power BI / Tableau ??

• Querying and transforming data
• Data modeling
• Calculations and Formula
• Reports and Visualizations
• Dashboards

6. Data Preparation and Validation ??

• Data collection
• Data discovery and profiling
• Data cleansing
• Data transformation
• Data validation and publishing

7. Exploratory Analysis and Modeling ???

• Regressions
• Classification
• Clustering

8. Machine Learning Libraries ??

• Scikit-Learn
• PyTorch
• TensorFlow

9. Data Storytelling ??

Using human communication to help your audience develop a connection to the information

For more on data storytelling, read my article on ?? The Art of Data Storytelling