Training on SQL for Data Manipulation and Processing

Module 1: Introduction to Databases and SQL Fundamentals

• Overview of relational database systems
• Database concepts: tables, keys, and relationships
• Writing basic SQL queries (SELECT, FROM, WHERE)
• Case Study: Extracting employee data from a corporate HR database

Module 2: Data Retrieval, Filtering, and Aggregation

• Using aggregate functions: SUM, AVG, COUNT, MAX, MIN
• Grouping data with GROUP BY and filtering with HAVING
• Sorting and conditional statements (CASE, IF)
• Case Study: Summarizing monthly sales and regional performance data

Module 3: Working with Multiple Tables and Joins

• Types of joins: INNER, LEFT, RIGHT, and FULL OUTER
• Combining data across different schemas
• Managing many-to-many relationships
• Case Study: Integrating customer and transaction datasets for analysis

Module 4: Subqueries, CTEs, and Views

• Using subqueries in SELECT, FROM, and WHERE clauses
• Common Table Expressions (CTEs) for complex queries
• Creating and managing database views
• Case Study: Building reusable SQL views for project dashboards

Module 5: Data Manipulation and Cleaning

• Inserting, updating, and deleting records
• Handling duplicates, null values, and inconsistencies
• Normalization and denormalization of tables
• Case Study: Cleaning and standardizing program monitoring data

Module 6: Advanced SQL Functions and Data Transformation

• String, date, and numeric manipulation functions
• Using window functions (RANK, ROW_NUMBER, LAG, LEAD)
• Derived columns and calculated fields
• Case Study: Creating time-based reports using sales trend data

Module 7: Query Optimization and Performance Tuning

• Understanding query execution plans
• Indexing strategies for performance
• Reducing redundancy and improving speed
• Case Study: Optimizing a slow-running financial report query

Module 8: Automating Data Workflows and Stored Procedures

• Creating and executing stored procedures
• Automating data imports, updates, and exports
• Error handling and scheduling scripts
• Case Study: Automating monthly data consolidation for management reports

Module 9: SQL for Data Analytics and Reporting

• Building analytical queries for BI dashboards
• Integrating SQL with Power BI, Excel, or Python
• Creating report-ready datasets
• Case Study: Generating KPI-based performance dashboards from SQL queries

Module 10: Data Security, Governance, and Final Project

• User permissions and access control
• Data integrity and compliance best practices
• Final project: End-to-end data processing and reporting exercise
• Case Study: Implementing a secure SQL data pipeline for an organization