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Databricks Databricks-Certified-Data-Engineer-Professional Korean Exam Overview:

Certification Vendor:Databricks
Exam Name:Databricks Certified Data Engineer Professional Exam
Exam Number:Databricks-Certified-Data-Engineer-Professional
Exam Duration:120 minutes
Exam Price:$200 USD
Related Certifications:Databricks Certified Data Engineer Associate
Exam Format:Proctored online exam, Multiple choice, Multiple select, Scenario-based questions
Available Languages:English
Passing Score:70%
Real Exam Qty:45-60
Certificate Validity Period:2 years
Recommended Training:Delta Lake Fundamentals
Databricks Data Engineer Learning Path
Exam Registration:Databricks Certification Portal
Databricks Academy
Sample Questions: DOWNLOAD DEMO
Exam Way:Online proctored exam via Databricks certification platform
Pre Condition:Recommended: Databricks Certified Data Engineer Associate or equivalent hands-on experience with Spark and Delta Lake
Official Syllabus URL:https://www.databricks.com/learn/certification/data-engineer-professional

Databricks Databricks-Certified-Data-Engineer-Professional Korean Exam Syllabus Topics:

SectionObjectives
Data Ingestion and Processing- Structured Streaming fundamentals
- Batch and streaming ingestion with Auto Loader
- ETL pipeline design patterns
Databricks Lakehouse Platform Architecture- Workspace and cluster architecture
- Medallion architecture (Bronze, Silver, Gold)
- Data governance concepts (Unity Catalog basics)
Data Modeling and Transformation- Dimensional modeling concepts
- Spark SQL transformations
- Performance optimization techniques
Delta Lake and Data Management- Schema evolution and enforcement
- Time travel and versioning
- Delta Lake transactions and ACID properties
Production Pipelines and Orchestration- Databricks Workflows
- Job scheduling and monitoring
- Error handling and recovery strategies

Your Databricks Certified Data Engineer Professional Exam (Databricks-Certified-Data-Engineer-Professional Korean Version) Questions Answered in Full

At present, the Databricks-Certified-Data-Engineer-Professional Korean exam's passing score is 70%, and registration costs $200 USD. Since failing means registering again at full price, thorough preparation is the economical choice — and Databricks can revise both figures, so confirm them officially before booking.

The Databricks Certified Data Engineer Professional Exam (Databricks-Certified-Data-Engineer-Professional Korean Version) blueprint is built around these main domains:

  • Databricks Lakehouse Platform Architecture
  • Delta Lake and Data Management
  • Data Ingestion and Processing

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Databricks publishes these prerequisites for the Databricks Certified Data Engineer Professional Exam (Databricks-Certified-Data-Engineer-Professional Korean Version): Recommended: Databricks Certified Data Engineer Associate or equivalent hands-on experience with Spark and Delta Lake.

Verify the current requirements on the official certification page.

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Databricks Certified Data Engineer Professional Exam (Databricks-Certified-Data-Engineer-Professional Korean Version) Sample Questions:

Question #1

날씨 기록을 저장하는 Delta 테이블은 날짜별로 분할되어 있으며 다음과 같은 스키마를 가지고 있습니다.
날짜(DATE), 장치 ID(INT), 온도(FLOAT), 위도(FLOAT), 경도(FLOAT)
북극권 내의 모든 기록을 찾으려면 아래 필터를 사용하여 쿼리를 실행합니다.
위도 > 66.3
다음 중 Delta 엔진이 로드할 파일을 식별하는 방법을 설명하는 문장은 무엇입니까?

  • A. 모든 레코드는 연결된 저장소에 캐시된 후 필터가 적용됩니다.
  • B. Hive 메타스토어에서 위도 열의 최소값과 최대값 통계를 검색합니다.
  • C. Parquet 파일의 바닥글을 스캔하여 위도 열의 최소값과 최대값 통계를 확인합니다.
  • D. 모든 레코드가 운영 데이터베이스에 캐시된 후 필터가 적용됩니다.
  • E. 델타 로그에서 위도 열의 최소값과 최대값 통계를 확인합니다.
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

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Question #2

데이터 엔지니어가 이메일 주소가 포함된 열을 마스킹하고 있습니다. 목표는 모든 행에 대해 동일한 길이의 출력 문자열을 생성하되, 각 이메일 값에 따라 다른 출력 문자열을 생성하는 것입니다.
이를 위해 어떤 SQL 함수를 사용해야 할까요?

  • A. mask(이메일, '?')
  • B. sha2(이메일, 0)
  • C. sha1(이메일)
  • D. 해시(이메일)
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #3

데이터 엔지니어가 스트리밍 주문 데이터를 처리하기 위해 Lakeflow 선언적 파이프라인을 설계하고 있습니다.
이 파이프라인은 자동 로더(Auto Loader)를 사용하여 데이터를 수집하며, customer_id와 amount 값이 0보다 큰지 확인하여 데이터 품질을 보장해야 합니다. 유효하지 않은 레코드는 삭제해야 합니다. Python을 사용하여 이 요구 사항을 구현하는 Lakeflow 선언적 파이프라인 구성은 무엇입니까?

  • A. @dlt.table
    def silver_orders():
    반품 (
    dlt.read_stream("bronze_orders")
    .expect_or_drop("valid_customer", "customer_id IS NOT NULL")
    .expect_or_drop("valid_amount", "amount > 0")
    )
  • B. @dlt.table
    def silver_orders():
    반품 (
    dlt.read_stream("bronze_orders")
    .expect("valid_customer", "customer_id IS NOT NULL")
    .expect("valid_amount", "amount > 0")
    )
  • C. @dlt.table
    @dlt.expect_or_drop("valid_customer", "customer_id IS NOT NULL")
    @dlt.expect_or_drop("valid_amount", "amount > 0")
    def silver_orders():
    dlt.read_stream("bronze_orders")를 반환합니다.
  • D. @dlt.table
    @dlt.expect("valid_customer", "customer_id가 NULL이 아닙니다")
    @dlt.expect("valid_amount", "amount > 0")
    def silver_orders():
    dlt.read_stream("bronze_orders")를 반환합니다.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

데이터 엔지니어가 데이터브릭스(Databricks)에서 데이터 도착이 지연되는 경우가 흔한 카프카(Kafka) 스트림의 레코드를 처리하는 파이프라인을 설계하고 있습니다. 이 경우 어떤 접근 방식을 사용해야 할까요?

  • A. 예상 도착 시간 이후에 도착하는 레코드를 수용하기 위해 허용되는 지연 시간을 지정하는 워터마크를 사용하여 정확한 집계 및 상태 관리를 보장합니다.
  • B. Databricks Jobs를 사용하여 모든 과거 데이터를 주기적으로 재처리하는 사용자 지정 솔루션을 구현합니다.
  • C. 배치 테이블이 있는 Auto CDC 파이프라인을 사용하여 지연 데이터 처리를 간소화합니다.
  • D. 일괄 처리를 사용하여 매번 전체 출력 테이블을 덮어쓰므로 늦게 도착한 데이터도 정확하게 반영됩니다.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #5

데이터 엔지니어링 팀이 Delta Lake를 사용하여 추가 전용 데이터 파이프라인을 구현하고 있으며, 한 번 기록된 데이터는 절대 수정되거나 삭제되지 않도록 하려고 합니다. 기존 데이터의 수정을 방지하려면 데이터 엔지니어는 Delta Lake의 어떤 기능을 활성화해야 할까요?

  • A. 델타 최적화
  • B. 델타 타임 트래블
  • C. 델타 추가 전용
  • D. 델타 진공
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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