The Complete SQL & Power BI Bootcamp: Become a Data Analyst

Install and set up MySQL server and MySQL Workbench to run a local MySQL instance. Use the Workbench UI to write and execute queries and view results.

Create your first database and an employee table in MySQL Workbench, learn how databases and tables connect, and apply data types like varchar and int to keep data clean.

Practice CRUD operations on the employee table using insert into, select, update, and delete from with a where clause in SQL, guided by real-world data management examples.

Explore sql constraints as rules that guard data integrity, focusing on the not null constraint and introducing primary key, foreign key, unique, default, and check constraints.

Explore unique, default, and check constraints in SQL to keep data clean, reliable, and error-free. Learn practical examples with email uniqueness, automatic defaults, and age checks (18–60) in SQL Workbench.

Learn how the primary key uniquely identifies each record, cannot be null or duplicate, and is defined with autoincrement in the employee records example.

Explore how foreign key constraints link employees to departments by referencing department primary keys, ensuring referential integrity. Learn practical syntax and common errors, such as autoincrement and primary key requirements.

Learn how the where clause filters data from tables using operators like greater than, less than, between, in, and like, and apply it with select, update, and delete statements.

Master SQL aggregate functions—count, sum, avg, min, and max—to summarize data across rows. Apply them with where and group by to analyze totals, averages, and ranges by department or age.

Discover how the group by clause aggregates data by department using count, sum, average, min, and max, with where filtering and aliases for Power BI or Excel reports.

Learn how the having clause filters groups after a group by, using total salary per department and department headcounts. Compare where and having to filter rows versus groups.

Learn common mistakes with the having clause, including using having without group by, mixing where and having, and forgetting aggregate functions; master correct sequence after grouping.

Sort data with the order by clause using asc or desc. Sort by multiple columns, including aliases, and place it after where, group by, and having.

Use the limit clause to restrict the number of rows returned, with order by and offset for pagination. Apply it to show top salaries or latest users while preserving data.

Explore how SQL joins unify data from multiple tables using inner join, left join, right join, and full join via union, with practical employee and department examples.

Explore practical SQL queries that join multiple tables using inner, left, and full joins to connect employee, department, and project data, and compute total salaries by department.

Master subqueries to fetch data within another query, use them in where clauses and select statements, and compare salaries against the average to filter employees.

Learn how to use SQL case statements to categorize data, convert codes to meaningful text, and perform conditional calculations like salary bonuses with practical examples.

Use the alter table command to add columns, modify data types or sizes, rename columns, drop columns, or rename the table itself, as shown with an employee table.

Explore window functions such as row_number, rank, and dense_rank, using over, partition by, and order by to rank rows within groups without collapsing data.

Use common table expressions, introduced by with keyword, to create a temporary result set, reference it in a main query, and simplify complex, repetitive SQL without persisting data.

Create views as permanent, reusable versions of ctes, acting as virtual tables that do not store data, enabling simplified, secure, focused queries.

Learn how indexing speeds up SQL queries by where, join, or order by clauses, and explore normal, unique, composite, primary key, and full text indexes with practical examples.

Power BI is a Microsoft business analytics and data visualization tool that connects to data sources, transforms data, and visualizes insights with drag-and-drop dashboards and real-time updates.

Import data into Power BI from Excel and CSV, load tables, view data in data view, and connect tables by customer ID, with best practices for clean imports.

Harness Power Query basics to clean and transform data in Power BI. Remove unwanted columns, rename and change data types, merge and split columns, and load clean data for insights.

Set up Power BI data models by creating relationships using common fields, emphasizing one-to-many links between dimension and fact tables within a star schema to improve analysis.

learn how to create calculated columns in Power BI using DAX to derive new row-level data, categorize sales, concatenate fields, and extract year from dates.

Explore the difference between measures and calculated columns in Power BI, learn when to use each for dynamic vs fixed results under filters, and apply practical examples and visuals.

Explore three core Dax functions—sum, count rows, and distinct count—to calculate totals, row counts, and unique values in Power BI visuals, with hands-on examples using total price and sales data.

Explore how to implement time intelligence in Power BI by using a dedicated date table to perform YTD and MTD calculations, and compare this year with last year.

Build KPI cards in Power BI by creating measures for total sales, total orders, and total customers, and filter them with a product slicer to track performance.