Databricks Certified Data Engineer Associate Practice Exam

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The minimally qualified candidate should be able to: Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools, including: 24 % (11/45)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: 29% (13/45)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 Py Spark and Spark SQL)Incrementally process data, including: 22% (10/45)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: 16% (10/45)Jobs (scheduling, task orchestration, UI)Dashboards (endpoints, scheduling, alerting, refreshing)Understand and follow best security practices, including: 9% (4/45)Unity Catalog (benefits and features)Entity Permissions (team-based permissions, user-based permissions)Duration Testers will have 90 minutes to complete the certification exam. Questions There are 45 multiple-choice questions on the certification exam. The questions will be distributed by high-level topic in the following way: Databricks Lakehouse Platform – 24% (11/45)ELT with Spark SQL and Python – 29% (13/45)Incremental Data Processing – 22% (10/45)Production Pipelines – 16% (7/45)Data Governance – 9% (4/45)