Databricks - Master Azure Databricks for Data Engineers

🌟 Course Title: Databricks - Master Azure Databricks for Data Engineers

🚀 About the Course

Embark on a comprehensive learning journey with our "Databricks - Master Azure Databricks for Data Engineers" course. Designed to elevate your data engineering expertise, this program leverages the robust Azure cloud platform and focuses on hands-on experience with PySpark and Spark SQL. 🛠️✨

What You'll Learn:

• Databricks in Azure Cloud: Gain a solid understanding of how Databricks integrates within the Azure ecosystem.
• Working with DBFS and Mounting Storage: Master the art of data storage using Databricks Distributed File System (DBFS) and its mounting capabilities.
• Unity Catalog - Configuring and Working: Learn to configure and efficiently work with Unity Catalogs, managing data access and permissions.
• Unity Catalog User Provisioning and Security: Understand the security aspects and user provisioning within Unity Catalogs to ensure secure data management.
• Working with Delta Lake and Delta Tables: Dive deep into Delta Lake's architecture, understand its benefits, and work with Delta Tables for a robust data handling solution.
• Manual and Automatic Schema Evolution: Learn manual schema evolution techniques and set up automatic schema evolution pipelines.
• Incremental Ingestion into Lakehouse: Explore incremental ingestion methods to efficiently update data within the lakehouse architecture.
• Databricks Autoloader: Utilize the Databricks Autoloader for automated ETL processes.
• Delta Live Tables and DLT Pipelines: Understand how Delta Live Tables work in real-time processing and create Delta Lakes pipelines.
• Databricks Repos and Databricks Workflow: Get familiar with Databricks' repository system and set up a Databricks workflow for streamlined project management.
• Databricks Rest API and CLI: Learn to interact with your Databricks workspace using the REST API and Command Line Interface for automation and scaling.

🏆 Capstone Project

Put your skills to the test with an End-To-End Capstone project that simulates a real-life data engineering scenario. You'll design, code, implement, test, and set up CI/CD for your solution, applying best practices throughout the process. 🛠️💻

Who Should Take This Course?

This course is tailored for:

• Data Engineers: Aiming to develop Lakehouse projects using the Medallion architecture approach with Databricks.
• Data and Solution Architects: Responsible for designing and building the organization's Lakehouse platform infrastructure on Azure.
• Managers/Architects: Overseeing the implementation of Lakehouse solutions at a granular level.

Spark Version and Environment

This course is built on real-world applications using:

• Databricks in Azure Cloud for a scalable, secure, and collaborative cloud environment.
• Apache Spark 3.5, the latest version that offers enhanced performance and features for data processing.
• Databricks Runtime 13.3, ensuring all examples and code are compatible with the Azure Databricks Cloud environment.

🌈 Join us now and transform your approach to data engineering with Azure Databricks! Let's unlock the power of big data together! 🚀💫