SQL & MySQL for Data Analytics: Beginner to Professional

Explore joining tables with foreign keys in MySQL by mapping customer and product IDs in an orders table, add constraints, and insert sample data to enable data analytics.

Master the select and where clauses to fetch data and filter results using specific columns, with in list, like patterns, and between ranges.

Sort results with order by, arranging by price or name in ascending or descending order. Use limit to show the top 10 most expensive products, ideal for exports and dashboards.

Learn to apply conditional and logical operators in SQL, using and, or, not, and like to filter data with where clauses, including electronics over 300 and names starting with A.

Discover aliasing to rename columns with the as keyword, including a price with tax example (price times 1.19); it enhances readability in long queries and across joins.

Group data by category in SQL to summarize items per category. Apply min, max, average, and count with aliases to reveal cheapest, most expensive, and total values per category.

Learn how to filter aggregated results after grouping by category using the having clause, to show categories with more than five products using count and other aggregate functions.

Use the distinct keyword to return unique values in SQL queries. Count unique customers by combining count with distinct in the orders table.

Learn how inner joins connect orders and customers by matching foreign keys and primary keys such as customer_id, using aliases to improve readability.

Learn to link orders, customers, and products using inner join and join syntax, display order id, product name, and quantity, and extend queries to three-table joins.

Identify and manage null values in MySQL to ensure clean reports, using is null, is not null, and replacing nulls with uncategorized, plus using aliases in inner joins.

Learn to standardize and clean data using MySQL string functions such as upper, lower, trim, concat, substring, replace, and locate to format text, measure length, and validate emails.

Explore subqueries and nested select statements to compute the global average, compare each customer's spending against it, and show the difference, all without using joins.

Explore window functions in SQL, learn to rank customers by total spending with rank and dense_rank, partition by city, and compute running totals for cumulative spending.

Analyze how correlated subqueries rank customers within each city by comparing outer and inner tables, counting higher spenders, and comparing performance to window functions and cte alternatives.

Learn practical database design using entity relationship diagrams in draw.io, defining entities and attributes, keys, and relationships among customers, orders, shipments, products, suppliers, and employees.

Map one-to-many and many-to-many relationships among customers, orders, employees, products, and suppliers using primary keys, foreign keys, and the order items bridge table.

From scratch, design a relational model by building an entity relationship diagram for a consulting firm, defining clients, employees, projects, invoices, and payments, with SQL and denormalization-aware analysis.

Create the physical database schema in mysql by building clients, employees, projects, and invoices tables, with cascading and set-null relationships, then populate and analyze the data.

Connect your MySQL data to Power BI and visualize it in the report view. Build visuals by leveraging table relationships, data types, and automatic aggregation to reveal client budgets.

Learn to create and customize Power BI slicers to filter visuals by city, country, or industry, apply exact filter interactions, and design user-friendly dashboards.

Define kpis and calculated measures to drive a project and revenue insights dashboard. Visualize total revenue, invoice amount, and outstanding balance from payments and invoices.

Create a dashboard with revenue by client, city map with bubble sizes by amount, and a monthly line chart that filters visuals and shows detailed tooltips.

Format and enhance the dashboard by resizing text, aligning elements, renaming charts, and applying bold fonts and themes to clearly present revenue by city and monthly totals.

Connect MySQL data to Power BI to build interactive dashboards with slicers and filters, and transform clean data and SQL queries into actionable business insights.