Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version): Databricks-Certified-Professional-Data-Engineer Exam
"Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version)", also known as Databricks-Certified-Professional-Data-Engineer exam, is a Databricks Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 217 Q&As to your Databricks-Certified-Professional-Data-Engineer Exam preparation. In the Databricks-Certified-Professional-Data-Engineer exam resources, you will cover every field and category in Databricks Certification Certification helping to ready you for your successful Databricks Certification.
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- Exam Code: Databricks-Certified-Professional-Data-Engineer
- Exam Name: Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version)
- Certification Provider: Databricks
- Corresponding Certification: Databricks Certification
- Updated: Sep 19, 2026
- No. of Questions: 217 Questions & Answers with Testing Engine
- Download Limit: Unlimited
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Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam Overview:
| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Professional Data Engineer Exam |
| Exam Number: | Databricks-Certified-Professional-Data-Engineer |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple select, Multiple choice, Scenario-based questions |
| Passing Score: | 70% |
| Certificate Validity Period: | 2 years |
| Available Languages: | English |
| Real Exam Qty: | 60-70 |
| Exam Price: | USD 200 |
| Related Certifications: | Databricks Certified Data Engineer Associate |
| Recommended Training: | Databricks Academy |
| Exam Registration: | Databricks Certification Portal |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam |
| Pre Condition: | Recommended: Databricks Certified Data Engineer Associate or equivalent experience with Spark and Databricks platform. |
| Official Syllabus URL: | https://www.databricks.com/learn/certification |
Databricks Databricks-Certified-Professional-Data-Engineer Korean Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Production Pipelines and Orchestration | - Automate ETL pipelines and scheduling - Build and manage workflows using Databricks Jobs - Pipeline reliability and fault tolerance |
| Data Ingestion and Transformation | - Transform and clean datasets using Spark SQL and DataFrame APIs - Handle batch and streaming data pipelines - Ingest data using Apache Spark and Databricks |
| Data Modeling and Storage | - Design scalable data lakehouse architectures - Schema evolution and data partitioning strategies - Delta Lake table design and optimization |
| Security, Governance, Monitoring, and Optimization | - Monitor and optimize Spark workloads - Cost optimization and performance tuning - Implement Unity Catalog governance and access control |
Frequently Asked Questions: Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) Exam
The Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) exam requires 70% to pass, and registration costs USD 200. A failed attempt means paying the same fee again — a readiness check with the PrepPDF engines before booking is the cheaper option.
Databricks recommends these training resources for the Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) exam:
Follow the training with steady self-testing — the 217 practice questions from PrepPDF help you apply theory and fill any gaps the training leaves.
The Databricks-Certified-Professional-Data-Engineer Korean exam is a Databricks certification exam validating the Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) syllabus shown above. It belongs to these credential paths: Databricks Certified Data Engineer Associate. Candidates in 2026 prepare for it with PrepPDF's 217 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
PrepPDF issues a full refund if you take the Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) exam within 60 days of purchase and do not pass. The policy does not apply if the exam is taken within 3 days of purchase, if the exam was never actually taken, or to free materials or expired orders, and the candidate name must match the payer name. Submit a scan of your enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, exchange for two free exam products of equal value and keep your original update service. Orders arrive by email within 1 minute — contact support if nothing arrives within 2 hours.
Online proctored exam Register for the Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) exam through these official channels:
After booking, PrepPDF delivers your practice questions within 1 minute — preparation starts the same day.
The Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) exam contains 60-70 to complete within 120 minutes. Timed simulation in the PrepPDF Desktop Test Engine teaches that rhythm before exam day does.
The official Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) outline defines 4 domains. The leading three are Production Pipelines and Orchestration, Data Ingestion and Transformation, and Data Modeling and Storage. The full list is in the topics section above, and PrepPDF's 217 practice questions cover each one.
Three versions of the same study materials: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows that simulates the real exam with two practice modes and works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 217 practice questions are identical across versions. Every purchase includes 365 days of free updates — whenever a new version is compiled, it is sent to you automatically — plus a 50% renewal discount afterward and unlimited computer installations.
Recommended: Databricks Certified Data Engineer Associate or equivalent experience with Spark and Databricks platform. Since requirements change over time, confirm the latest on the official Databricks exam page before scheduling.
Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer Korean Version) Sample Questions:
Databricks 작업이 3개의 태스크로 구성되었으며, 각 태스크는 Databricks 노트북입니다. 태스크 A는 다른 태스크에 종속되지 않습니다. 태스크 B와 C는 병렬로 실행되며, 각각 태스크 A에 직렬 종속성을 갖습니다.
작업 A가 예정된 실행 중에 실패할 경우, 이 실행 결과를 설명하는 문장은 무엇입니까?
- A. 작업 B와 C는 건너뛰게 됩니다. 작업 A에 표현된 일부 로직이 작업 실패 전에 실행되었을 수 있습니다.
- B. 작업 B와 C는 건너뛰어집니다. 단계 실패로 인해 작업 A는 변경 사항을 커밋하지 않습니다.
- C. 작업 B와 C는 구성된 대로 실행을 시도합니다. 작업 A에서 변경된 사항은 작업 실패로 인해 되돌려집니다.
- D. 모든 작업이 성공적으로 완료되지 않으면 레이크하우스에 변경 사항이 커밋되지 않습니다. 작업 A가 실패했으므로 모든 커밋은 자동으로 롤백됩니다.
- E. 모든 작업은 종속성 그래프로 관리되므로 모든 작업이 성공적으로 완료될 때까지 레이크하우스에 변경 사항이 커밋되지 않습니다.
Correct Answer: A 🗳️
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데이터 엔지니어가 사용자 ID별로 그룹화된 대규모 사용자 활동 로그에 대해 groupBy 집계를 실행하고 있습니다. 일부 사용자는 수백만 건의 기록을 보유하고 있어 작업 불균형과 긴 실행 시간을 초래하고 있습니다.
이 집계의 불균형을 바로잡을 수 있는 기술은 무엇일까요?
- A. 셔플을 방지하려면 groupBy 대신 reduceByKey를 사용하세요.
- B. Spark 드라이버 메모리를 늘리고 다시 시도하십시오.
- C. 집계 전에 왜곡된 키에 임의의 접두사를 추가하여 솔팅을 적용한 다음, 접두사를 제거한 후 다시 집계합니다.
- D. 집계 전에 편향된 사용자를 필터링합니다.
Correct Answer: C 🗳️
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3개의 실행기 노드로 구성된 특정 클러스터의 Ganglia 메트릭을 평가할 때, 어떤 지표가 VM 리소스의 적절한 활용을 나타낼까요?
- A. CPU 사용률은 약 75%입니다.
- B. 총 디스크 공간은 일정하게 유지됩니다.
- C. 수신 바이트는 초당 8천만 바이트를 초과하지 않습니다.
- D. 5분 평균 부하량이 일정하게 유지됩니다/평탄하게 유지됩니다
- E. 네트워크 I/O는 절대 급증하지 않습니다.
Correct Answer: A 🗳️
데이터 엔지니어가 Lakeflow Declarative Pipelines의 Expectations 기능을 사용하여 수신되는 센서 데이터의 품질을 추적하고 있습니다. 센서에서 주기적으로 범위를 벗어난 잘못된 측정값이 전송되는데, 현재는 해당 행에 경고 플래그를 지정하고 정상 데이터와 함께 실버 테이블에 기록하고 있습니다. 그런데 새로운 요구 사항이 생겼습니다. 잘못된 행을 별도의 격리 테이블에 저장하고 더 이상 실버 테이블에 포함시키지 않아야 한다는 것입니다.
이것은 그들의 은색 테이블에 대한 기존 코드입니다:
@dlt.table
@dlt.expect( " valid_sensor_reading " , " reading < 120 " )
def silver_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
What code will satisfy the requirements?
- A. @dlt.table
@dlt.expect_or_drop( " valid_sensor_reading " , " reading < 120 " )
def silver_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
@dlt.table
@dlt.expect( " invalid_sensor_reading " , " reading > = 120 " )
def quarantine_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " ) - B. @dlt.table
@dlt.expect_or_drop( " valid_sensor_reading " , " reading < 120 " )
def silver_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
@dlt.table
@dlt.expect( " invalid_sensor_reading " , " reading < 120 " )
def quarantine_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " ) - C. @dlt.table
@dlt.expect_or_drop( " valid_sensor_reading " , " reading < 120 " )
def silver_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
@dlt.table
@dlt.expect_or_drop( " invalid_sensor_reading " , " reading > = 120 " ) def quarantine_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " ) - D. @dlt.table
@dlt.expect( " valid_sensor_reading " , " reading < 120 " )
def silver_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
@dlt.table
@dlt.expect( " invalid_sensor_reading " , " reading > = 120 " )
def quarantine_sensor_readings():
return spark.readStream.table( " bronze_sensor_readings " )
Correct Answer: D 🗳️
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한 조직이 웹 및 모바일 애플리케이션에서 고객 데이터를 처리합니다. 데이터에는 이름, 이메일, 전화번호 및 위치 기록이 포함됩니다. 데이터는 배치 파일(SFTP를 통해 매일 전송)과 스트리밍 JSON 이벤트(Kafka를 통해 실시간으로 전송) 형태로 수신됩니다.
데이터 개인정보 보호 정책을 준수하려면 다음 요건을 충족해야 합니다.
* 이메일, 전화번호, IP 주소와 같은 개인 식별 정보(PII)는 저장하기 전에 마스킹 또는 익명화해야 합니다.
* 배치 파이프라인과 스트리밍 파이프라인 모두 개인정보 처리 방식에 일관성을 적용해야 합니다.
* 마스킹 로직은 감사 가능하고 재현 가능해야 합니다.
* 마스킹된 데이터는 후속 분석에 계속 사용할 수 있어야 합니다.
데이터 엔지니어는 배치 모드와 스트리밍 모드를 모두 지원하고, 개인 식별 정보(PII)에 데이터 마스킹을 적용하며, 감사 추적성을 유지하는 Databricks 기반의 규정 준수 데이터 파이프라인을 어떻게 설계해야 할까요?
- A. Lakeflow 선언적 파이프라인을 사용하여 배치 및 스트리밍 데이터를 모두 수집하고, 수집 중에 데이터가 수정되지 않도록 읽기 시점에 Unity 카탈로그 열 마스크를 통해 마스킹을 적용합니다.
- B. 노트북을 사용하여 배치 데이터를 로드하고 SQL Warehouses를 사용하여 스트리밍 데이터를 수집합니다. 저장 후 Silver 테이블에서 Unity Catalog 열 마스크를 사용하여 필드를 수정합니다.
- C. 배치 및 스트리밍 데이터 수집을 위해 Lakeflow 선언적 파이프라인을 사용하고, 개인 식별 정보(PII) 마스킹 기능을 정의합니다.
그리고 델타 호수에 편지를 쓰기 전에 청동을 섭취하는 동안 그것을 적용하십시오. - D. 계보 추적을 위해 Bronze 테이블에는 개인 식별 정보(PII)를 마스킹하지 않고 저장한 다음, 보고에 사용되는 Gold 테이블에서 마스킹 로직을 적용합니다.
Correct Answer: C 🗳️
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