Databricks Certified Data Engineer Associate - Preparation




Databricks Certified Data Engineer Associate - Preparation

If you are interested in becoming a Certified Data Engineer Associate 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:

  • Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including:

    • Data Lakehouse (architecture, descriptions, benefits)

    • Data Science and Engineering workspace (clusters, notebooks, data storage)

    • Delta Lake (general concepts, table management and manipulation, optimizations)

  • Build ETL pipelines using Apache Spark SQL and Python, including:

    • Relational entities (databases, tables, views)

    • ELT (creating tables, writing data to tables, cleaning data, combining and reshaping tables, SQL UDFs)

    • Python (facilitating Spark SQL with string manipulation and control flow, passing data between PySpark and Spark SQL)

  • Incrementally process data, including:

    • Structured Streaming (general concepts, triggers, watermarks)

    • Auto Loader (streaming reads)

    • Multi-hop Architecture (bronze-silver-gold, streaming applications)

    • Delta Live Tables (benefits and features)

  • Build production pipelines for data engineering applications and Databricks SQL queries and dashboards, including:

    • Jobs (scheduling, task orchestration, UI)

    • Dashboards (endpoints, scheduling, alerting, refreshing)

  • Understand and follow best security practices, including:

    • Unity Catalog (benefits and features)

    • Entity Permissions (data objects Privileges)


With the knowledge you gain during this course, you will be ready to take the certification exam.

I am looking forward to meeting you!

Preparation course for Databricks Data Engineer Associate certification exam

Url: View Details

What you will learn
  • Understand how to use Databricks Lakehouse Platform and its tools
  • Build ETL pipelines using Apache Spark SQL and Python
  • Process data incrementally in batch and streaming mode

Rating: 4.73148

Level: All Levels

Duration: 4 hours

Instructor: Derar Alhussein


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