Databricks Data Engineer Associate Course with Practical Examples & Hands-On Training, Master Databricks Skills
Instructed by Vijay Gadhave 11 hours on-demand video, 1 article, 14 downloadable resources.
At 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, 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 (team-based permissions, user-based permissions)
Who this course is for:
- Anyone who wants to prepare for the Databricks Data Engineer Associate certification exam
- Students who wants to peruse a career in Data Engineering
- Professionals who wants to move from other technologies to Data Engineering
- Anyone who wants to start learning Databricks
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