SQL and PowerBI
SQL (Structured Query Language) is a standardized language used to manage and manipulate relational databases. It enables users to query, update, and manage data through commands categorized into Data Query Language (DQL), Data Definition Language (DDL), Data Manipulation Language (DML), and Data Control Language (DCL). SQL is essential for performing complex data operations, maintaining data integrity, and supporting data-driven decision-making.
Power BI is a powerful business analytics tool developed by Microsoft that enables users to visualize and share insights from their data. It connects to a variety of data sources, allowing users to import, transform, and model data with ease. Power BI offers a range of interactive visualizations and tools for creating dashboards, reports, and data stories. Its integration with SQL allows for seamless querying and analysis of large datasets, enhancing the ability to make informed business decisions based on real-time data.
Our mission
To empower individuals and organizations with robust tools and knowledge to efficiently manage, manipulate, and analyze relational data using SQL, fostering data-driven decision-making and operational excellence.
Our vision
To be the leading provider of SQL education and resources, cultivating a community of skilled data professionals who leverage SQL to drive innovation, optimize data management processes, and contribute to the advancement of data science and analytics across industries.
SQL
Module 1: Introduction to SQL and Databases
Overview of SQL and its importance in data science
Introduction to relational databases
Basic database concepts (tables, rows, columns, keys)
SQL syntax and structure
Installing and setting up a SQL environment
Basic SQL commands: `SELECT`, `FROM`, `WHERE`
Hands-on practice and Q&A
Module 2: Advanced Data Retrieval
- Filtering data with `WHERE` clause and logical operators
- Sorting results with `ORDER BY`
- Using `LIMIT` for result control
- Introduction to `DISTINCT`
- Combining conditions with `AND`, `OR`, `NOT`
- Hands-on exercises and Q&A
Module 3: Aggregation and Grouping
Aggregate functions: `COUNT`, `SUM`, `AVG`, `MIN`, `MAX`
Grouping data with `GROUP BY`
Filtering grouped data with `HAVING`
Combining aggregate functions with `GROUP BY`
Practical exercises and Q&A
Module 4: Working with Multiple Tables
Understanding joins: `INNER JOIN`, `LEFT JOIN`, `RIGHT JOIN`, `FULL JOIN`
Using aliases for readability
Combining multiple joins
Subqueries and nested queries
Hands-on practice with join queries and Q&A
Module 5: Data Manipulation
Inserting data into tables: `INSERT INTO`
Updating data: `UPDATE`
Deleting data: `DELETE`
Using transactions: `BEGIN`, `COMMIT`, `ROLLBACK`
Practical exercises and Q&A
Module 6: Advanced SQL Functions and Operators
- String functions: `CONCAT`, `SUBSTRING`, `UPPER`, `LOWER`
- Date and time functions: `NOW`, `DATE`, `DATEDIFF`
- Mathematical functions: `ROUND`, `CEIL`, `FLOOR`
- Conditional statements: `CASE WHEN`
- Practical exercises and Q&A
Module 7: Database Design and Normalization
Principles of database design
Normalization: 1NF, 2NF, 3NF
Creating and altering tables: `CREATE TABLE`, `ALTER TABLE`
Indexes and their importance
Foreign keys and constraints
Practical exercises and Q&A
Module 8: Performance Tuning and Advanced Topics
Query optimization techniques
Indexing strategies
Using views for simplified querying
Introduction to stored procedures and triggers
Best practices for writing efficient SQL
Final project: building a complete database query application
Review, wrap-up, and Q&A
Power BI
Module 1: Introduction to Power BI
Overview of Business Intelligence
Introduction to Power BI
Power BI Architecture and Components
Installing and Setting Up Power BI Desktop
Module 2: Data Preparation and Transformation
Connecting to Data Sources
Importing Data
Data Transformation with Power Query Editor
Module 3: Data Modeling
Understanding Data Models
Creating Relationships between Tables
Data Modeling Best Practices
Module 4: Introduction to DAX (Data Analysis Expressions)
Basic DAX Functions and Calculations
Advanced DAX for Data Analysis
Time Intelligence Functions
Module 5: Data Visualization
Introduction to Data Visualization in Power BI
Creating and Customizing Visuals
Using Charts, Tables, and Maps
Module 6: Interactive Dashboards
Designing Interactive Dashboards
Adding and Configuring Filters and Slicers
Creating Drill-Through and Drill-Down Reports
Module 7: Power BI Service and Integration
Publishing Reports to Power BI Service
Sharing and Collaborating on Reports
Creating and Managing Workspaces
Using Power BI Apps and Mobile View
Integrating Power BI with Other Tools (Excel, Azure, etc.)
Connecting Power BI to Live Data Sources
Module 8: Advanced Topics and Case Studies
Using AI Visuals and Insights
Implementing Row-Level Security (RLS)
Best Practices for Deploying Power BI Reports
Monitoring and Optimizing Performance
Managing Data Refresh and Gateways
Troubleshooting Common Issues
Real-Life Case Studies on Power BI Implementation
Hands-On Projects to Reinforce Learning
Creating a Comprehensive Power BI Solution from Scratch