Udemy – Databricks – Master Azure Databricks for Data Engineers 2024-1 – Downloadly

1. Databricks on Azure Cloud
2. Working with DBFS and mounting storage
3. Unity Catalog – Configuration and Operation
4. Unity Catalog User Provisioning and Security
5. Working with Delta Lake and Delta Tables
6. Manual and automatic schema development
7. Gradual swallowing at Lake House
8. Databricks Autoloader
9. Delta Live Tables and DLT Pipelines
10. Databricks Repos and Databricks Workflow
11. Databricks REST API and CLI

Capstone Project: This course also includes an end-to-end capstone project. This project will help you understand the actual project design, coding, implementation, testing, and CI/CD approach. Who will take this lesson? I designed this course for data engineers who want to develop Lakehouse projects following the Medallion architecture approach using the Databrick cloud platform. I am also creating this course for data and solution architects who are responsible for designing and building the organization’s Lakehouse platform infrastructure. Another group of people are managers and architects who are not directly involved in implementing Lake House, but they work with those who run Lake House on the ground floor. The version of Spark used in the course. This course uses Databricks on Azure Cloud and Apache Spark 3.5. I have tested all the source code and examples used in this course on Azure Databricks Cloud using Databricks Runtime 13.3.

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