Overview

These practice tests are designed to help you understand all of the exam syllabus for Databricks Certified Data Engineer Associate so you can pass the exam but also help you learn the concepts of the Databricks platform.The questions in each of the practice tests are on par with the actual exam questions you will be facing during the exam.I can assure you that you can pass with more than 90% if you understand the questions well. This is purely questions oriented syllabus covering tests,You have to go through the explanations after each attempt so that you will get the concepts and will be ready to face any twisted question from the topic.note: Go through Databricks partner academy course first and attempt this test for maximum efficiency of utilization of the course.Brief description on the exam:The Databricks Certified Data Engineer Associate certification exam assesses an individual's ability to use the Databricks Lakehouse Platform to complete introductory data engineering tasks. This includes an understanding of the Lakehouse Platform and its workspace, its architecture, and its capabilities. It also assesses the ability to perform multi-hop architecture ETL tasks using Apache Spark SQL and Python in both batch and incrementally processed paradigms. Finally, the exam assesses the tester's ability to put basic ETL pipelines and Databricks SQL queries and dashboards into production while maintaining entity permissions. Individuals who pass this certification exam can be expected to complete basic data engineering tasks using Databricks and its associated toolsThe candidate should be able to:Understand how to use and the benefits of using the Databricks Lakehouse Platform and its tools,: 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 PySpark 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)DurationExam participants will have 90 minutes to complete each practice exam with 45 multiple choice questions.QuestionsThere are 45 multiple-choice questions on each practice 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 - 24% (11/45)Production Pipelines - 16% (7/45)Data Governance - 7% (3/45)

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