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 Databricks Certified Data Engineer Professional -Preparation

Databricks Certified Data Engineer Professional -Preparation

Databricks Certified Data Engineer Professional -Preparation

Databricks Certified Data Engineer Professional -Preparation

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


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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


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 pipelines


Building incrementally processed ETL pipelines


Deduplicating data


Using Change Data Capture (CDC) to propagate changes


Optimizing workloads


Understand 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 ACLs


Creating row- and column-oriented dynamic views to control user/group access


Securely delete data as requested according to GDPR & CCPA


Configure alerting and storage to monitor and log production jobs, including:


Recording logged metrics


Debugging errors


Follow best practices for managing, testing and deploying code, including:


Relative imports


Scheduling Jobs


Orchestration Jobs




With 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


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