SQL_and_Databricks_Presentation_from_basic

SQL_and_Databricks_Presentation_from_basic

• 1.
  Introduction to SQLand SQL with Databricks Presented by: [Your Name] Team: [Your Team Name] Date: [Presentation Date]
• 2.
  Agenda • 1. Whatis SQL? • 2. Basic SQL Concepts & Commands • 3. SQL in Real-World Scenarios • 4. What is Databricks? • 5. Using SQL in Databricks • 6. Demo Use Case • 7. Q&A
• 3.
  What is SQL? •Structured Query Language • Used for managing and manipulating relational databases • Common RDBMS: MySQL, PostgreSQL, Oracle, SQL Server, Azure SQL DB
• 4.
  Basic SQL Concepts •SELECT: Retrieve data • WHERE: Filter data • JOIN: Combine data from multiple tables • GROUP BY / HAVING: Aggregate data • ORDER BY: Sort results • INSERT/UPDATE/DELETE: Modify data • DDL commands: CREATE, ALTER, DROP
• 5.
  Real-World SQL UseCases • Data extraction for reporting • Data validation and profiling • ETL and data pipelines • Business Intelligence dashboards
• 6.
  What is Databricks? •Cloud-based platform for data engineering, ML, and analytics • Built on Apache Spark • Supports multiple languages: SQL, Python, Scala, R • Unified platform for notebooks, jobs, and real-time processing
• 7.
  SQL in Databricks •SQL is fully supported in Databricks notebooks • Access Delta Tables using SQL queries • Use %sql magic command in notebooks • Connect to external sources: Azure SQL, PostgreSQL, ADLS
• 8.
  Databricks SQL Capabilities •Interactive dashboards • SQL editor with auto-complete • Scheduling and job runs • Query history and result caching
• 9.
  Databricks SQL Architecture •Workspace (control plane) • Clusters (compute layer) • Delta Lake (storage layer) • Unity Catalog (governance layer)
• 10.
  Sample Use Case •Load sales data into Delta Lake • Clean & aggregate data using SQL • Create dashboard using Databricks SQL editor
• 11.
  Benefits of SQLin Databricks • Scalability with Spark engine • Easy integration with cloud storage • Secure access control with Unity Catalog • Collaboration through notebooks
• 12.
  Demo (Optional) • Showa SQL query in Databricks notebook • Create a Delta Table • Run basic aggregations
• 13.
  Summary • SQL isessential for data manipulation • Databricks enhances SQL with scale and cloud-native features • Ideal for modern data analytics and engineering
• 14.
  Q&A • Open floorfor questions
• 15.
  Thank You • ContactInfo • Feedback request