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