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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.

Código de examen

Certified D

Duración

90 min

Questions

60

Requisitos previos oficiales

  • 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
Databricks Certified Data Engineer Associate

Profesiones específicas

Data Engineer ETL Developer Big Data Engineer Analytics Engineer
Artículos relacionados

Plano de dominio

El motor de simulación ExamBoot está sincronizado con el esquema del examen oficial. Nuestros bancos de preguntas adaptativos priorizan que usted alcance sus objetivos rápidamente..

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.

Dominio 5

Data Governance & Quality

17%
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.

Dominio 6

Data Governance & Quality (alternate phrasing)

17%
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.

Consejo de estudio

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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