Training on SQL for Data Science

Module 1: Introduction to SQL and Database Concepts

• Understanding databases, tables, records, and relationships
• Overview of relational database management systems (RDBMS)
• Introduction to SQL syntax, commands, and query structure
• Setting up SQL environments using MySQL, PostgreSQL, or SQL Server
• Writing and executing basic SQL statements
• Case Study: Exploring customer and sales databases for business reporting
• Practical Exercise: Install a database environment and create a simple database with tables

Module 2: Retrieving and Filtering Data with SQL

• Using SELECT statements to retrieve data
• Filtering records with WHERE, AND, OR, and BETWEEN
• Sorting and limiting results using ORDER BY and LIMIT
• Using aliases and distinct values in queries
• Applying pattern matching with LIKE and wildcards
• Case Study: Generating filtered sales and customer reports for decision-making
• Practical Exercise: Write queries to filter, sort, and retrieve records from sample datasets

Module 3: Advanced Querying and Table Relationships

• Understanding table relationships and joins
• Using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN
• Working with subqueries and nested queries
• Combining data from multiple tables efficiently
• Introduction to Common Table Expressions (CTEs)
• Case Study: Combining customer, orders, and payment datasets for business insights
• Practical Exercise: Build multi-table queries and generate relational reports

Module 4: Data Aggregation and Analytical Queries

• Grouping data using GROUP BY
• Using aggregate functions: COUNT, SUM, AVG, MIN, and MAX
• Filtering grouped data with HAVING
• Performing summary and trend analysis with SQL
• Creating business performance reports
• Case Study: Analyzing monthly revenue and product performance trends
• Practical Exercise: Create aggregation queries and summary dashboards using SQL results

Module 5: Managing and Modifying Data

• Inserting records using INSERT statements
• Updating and deleting records safely
• Understanding transactions and rollback operations
• Managing data integrity and database constraints
• Introduction to primary keys and foreign keys
• Case Study: Maintaining inventory and transaction records in a retail database
• Practical Exercise: Perform data insertion, updates, deletions, and transaction management tasks

Module 6: SQL Functions and Conditional Logic

• Working with string, numeric, and date functions
• Performing calculations and data formatting
• Using CASE statements for conditional logic
• Handling NULL values and missing data
• Creating reusable expressions in queries
• Case Study: Automating customer categorization and sales calculations
• Practical Exercise: Write SQL queries using built-in functions and conditional statements

Module 7: Database Design and Optimization

• Introduction to database normalization and denormalization
• Designing efficient database schemas
• Understanding indexes and query optimization
• Best practices for database performance and scalability
• Introduction to database documentation standards
• Case Study: Improving performance in a growing business database system
• Practical Exercise: Design a normalized database schema and optimize sample queries

Module 8: SQL for Data Analysis and Reporting

• Using SQL for business intelligence and reporting
• Cleaning and transforming data using SQL techniques
• Handling duplicates and missing records
• Creating analytical datasets for reporting tools
• Exporting SQL results for visualization and dashboards
• Case Study: Preparing business data for management reporting and analytics
• Practical Exercise: Perform data cleaning and transformation tasks on real-world datasets

Module 9: Real-World SQL Applications

• SQL applications in finance, healthcare, retail, and logistics
• Fraud detection and anomaly identification using SQL
• Customer segmentation and sales analysis
• Automating operational and management reports
• Best practices for working with large datasets
• Case Study: Identifying sales trends and customer purchasing behavior using SQL
• Practical Exercise: Analyze a business dataset and generate actionable insights using SQL queries

Module 10: Final SQL Project and Course Review

• End-to-end SQL project development
• Designing queries for business problem-solving
• Presenting SQL analysis findings and reports
• Review of key SQL concepts and best practices
• Case Study: Building a complete SQL reporting solution for organizational decision-making
• Practical Exercise: Develop and present a final SQL project using a real-world dataset