What is Databricks?

Databricks is a powerful platform designed for data engineering, data analysis, data science, and machine learning. It simplifies the complexities of distributed processing, leveraging Spark’s capabilities through native interfaces like Scala, R, Python, and SQL.

Features of Databricks

• Notebooks and Multilingual Support: Databricks allows you to work in collaborative notebooks where you can code in multiple languages, visualize data, and build interactive dashboards.
• Extensive Support and Documentation: Benefit from robust support and comprehensive documentation, making it easier to navigate and utilize the platform effectively.

Integration with Azure Services

• Azure Integration: Specifically, we’ll focus on Databricks within the Microsoft Azure ecosystem.
• Azure Data Lake Storage Gen2: Store and manage data efficiently using Azure Data Lake Storage Gen2.
• Azure DevOps and Repos: Implement source control and continuous integration/continuous deployment (CI/CD) pipelines using Azure DevOps and Repos.
• Azure Key Vault: Safely store and manage secrets required for secure operations.

Course Overview

This course dives deep into mastering Databricks, with a primary focus on practical applications and integration with Azure services:

1. Foundations of Databricks: Setting up your Azure account, Databricks instance, and data lake storage to kickstart your journey.
2. Spark SQL Operations: Learn essential operations in Spark SQL using Python (PySpark), including data manipulation and visualization.
3. Medallion Architecture and Data Organization: Understand the Medallion architecture for organizing data in a Data Lakehouse environment.
4. Delta Lake and Delta File Format: Explore Delta Lake for reliable and performant big data processing, leveraging transactional capabilities.
5. Delta Live Tables: Introduction to Delta Live Tables for building robust data processing pipelines.
6. Spark Structured Streaming: Real-time data processing capabilities using Spark’s structured streaming.
7. Automation and Collaboration: Utilize Databricks jobs, command-line interface (CLI), Git source control, and Databricks Repos for automation and team collaboration.
8. CI/CD with Databricks and Azure DevOps: Implement continuous integration and deployment pipelines to streamline development processes.

Conclusion

Mastering Databricks not only equips you with essential data engineering skills but also prepares you to integrate seamlessly with Azure services for scalable and efficient data solutions.