Databricks Certified Data Engineer Professional -Preparation

Preparation course for Databricks Data Engineer Professional certification exam with hands-on training

What you'll learn
Learn how to model data management solutions on Databricks Lakehouse
Build data processing pipelines using the Spark and Delta Lake APIs
Understand how to use and the benefits of using the Databricks platform and its tools
Build production pipelines using best practices around security and governance
Learn how to monitor and log production jobs
Follow best practices for deploying code on Databricks

Requirements
MUST HAVE - All the skills of an "Associate" Data Engineer on Databricks platform
If you feel you lack these skills, you should first study my preparation course on Udemy for the Associate-level certification. I covered there all the fundamental concepts of Databricks Lakehouse with hands-on training.

Description
If you are interested in becoming a Certified Data Engineer Professional from Databricks, you have come to the right place! I am here to helping you with preparing for this certification exam.By the end of this course, you should be able to:Model data management solutions, including:Lakehouse (bronze/silver/gold architecture, tables, views, and the physical layout)General data modeling concepts (constraints, lookup tables, slowly changing dimensions)Build data processing pipelines using the Spark and Delta Lake APIs, including:Building batch-processed ETL pipelinesBuilding incrementally processed ETL pipelinesDeduplicating dataUsing Change Data Capture (CDC) to propagate changesOptimizing workloadsUnderstand how to use and the benefits of using the Databricks platform and its tools, including:Databricks CLI (deploying notebook-based workflows)Databricks REST API (configure and trigger production pipelines)Build production pipelines using best practices around security and governance, including:Managing clusters and jobs permissions with ACLsCreating row- and column-oriented dynamic views to control user/group accessSecurely delete data as requested according to GDPR & CCPAConfigure alerting and storage to monitor and log production jobs, including:Recording logged metricsDebugging errorsFollow best practices for managing, testing and deploying code, including:Relative importsScheduling JobsOrchestration JobsWith the knowledge you gain during this course, you will be ready to take the certification exam.I am looking forward to meeting you!

Who this course is for:
Anyone aiming to pass the Databricks Data Engineer Professional certification exam,Junior Data Engineers on Databricks wanting to gain the skills of Professional Data Engineers