Docker Certified Associate – Preparation & methodology
Preparing for the Docker Certified Associate (DCA) exam is an achievable goal with the right plan, focused practice, and high-quality mock exams.
Databricks
Databricks Certified Data Engineer Associate
The Databricks Certified Data Engineer Associate certification validates an individual's ability to perform introductory data engineering tasks on the Databricks Lakehouse Platform.
Prüfungscode
Certified D
Dauer
90 min
Questions
60
Offizielle Voraussetzungen
- Hands-on experience with Apache Spark using PySpark or Scala (data transformations, joins, aggregations)
- Working knowledge of SQL for querying, joins, window functions, and performance tuning
- Familiarity with Databricks platform concepts: workspaces, clusters, notebooks, jobs, and Delta Lake
- Practical experience building ETL or data engineering pipelines and debugging production jobs
Gezielte Berufe
Data Engineer ETL Developer Big Data Engineer Analytics EngineerDomain-Blaupause
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Understand the Data Intelligence Platform and workspace, enable features that simplify data layout decisions and optimize query performance, and identify the appropriate compute for specific use cases.
Use Databricks Connect and Notebooks in data engineering workflows, classify valid Auto Loader sources and syntax, and apply built‑in debugging tools to ingest and troubleshoot data.
Implement the Medallion Architecture layers, select and configure clusters for performance, apply Lakeflow Spark Declarative Pipelines for ETL, use DDL/DML features, and compute complex aggregations with PySpark DataFrames.
Deploy and orchestrate Databricks Workflows (including asset bundles), repair and rerun failed tasks, leverage serverless managed compute, and analyze the Spark UI to optimize jobs.
Manage tables (managed vs external), assign permissions and roles within Unity Catalog, review audit logs and lineage, use Delta Sharing (types, advantages, limitations) and consider cost and Lakehouse Federation use cases.
Domäne 5
Data Governance & Quality
Manage tables (managed vs external), assign permissions and roles within Unity Catalog, review audit logs and lineage, use Delta Sharing (types, advantages, limitations) and consider cost and Lakehouse Federation use cases.
Domäne 6
Data Governance & Quality (alternate phrasing)
Explain differences between managed and external tables; identify grants, roles, audit logs, lineage, Delta Sharing types and cost considerations; and use Lakehouse Federation when connecting external sources.
Lerntipp
Use timed practice tests aligned to the exam blueprint, run focused weak-area drills with hands-on labs, complete timed blocks, and review test rationales thoroughly to cement concepts and identify gaps.
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