Udemy - Data Engineering with Spark Databricks Delta Lake Lakehouse

Requirements:

Some understanding of Database and SQL queries

Description:

Data Engineering is a vital component of modern data-driven businesses. The ability to process, manage, and analyze large-scale data sets is a core requirement for organizations that want to stay competitive. In this course, you will learn how to build a data pipeline using Apache Spark on Databricks' Lakehouse architecture. This will give you practical experience in working with Spark and Lakehouse concepts, as well as the skills needed to excel as a Data Engineer in a real-world environment.

Throughout the Course, You Will Learn:

Conducting analytics using Python and Scala with Spark.
Applying Spark SQL and Databricks SQL for analytics.
Developing a data pipeline with Apache Spark.
Becoming proficient in Databricks' free edition.
Managing a Delta table by accessing version history, restoring data, and utilizing time travel features.
Unity Catalog Volumes - File Storage and Operations
Optimizing query performance using Delta Cache.
Working with Delta Tables and Databricks File System.
Gaining insights into real-world scenarios from experienced instructors.

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