Microsoft Implementing a SQL Data Warehouse (70-767日本語版) : 70-767日本語

70-767日本語 pass collection

Exam Code: 70-767J

Exam Name: Implementing a SQL Data Warehouse (70-767日本語版)

Updated: Sep 12, 2026

Q & A: 170 Questions and Answers

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About Microsoft Implementing a SQL Data Warehouse (70-767日本語版) : 70-767日本語 Exam

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There is no prerequisite for this Microsoft 70-767 exam.

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70-767 Exam topics

Candidates must know the exam topics before they start of preparation. Because it will really help them in hitting the core. Our Microsoft 70-767 exam dumps will include the following topics:

  • Extract, transform and load data 40-45%
  • Build data quality solutions 15-20%
  • Design, implement and maintain a data warehouse 35-40%

Skills measured

  • Build data quality solutions (15-20%)
  • Extract, transform, and load data (40-45%)
  • Design, implement, and maintain a data warehouse (35-40%)

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Reference: https://www.microsoft.com/en-us/learning/exam-70-767.aspx

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Microsoft 70-767日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design, implement, and maintain a data warehouse35–40%- Design and implement indexes
  • 1. Choose appropriate indexing strategies
  • 2. Implement clustered, nonclustered, and columnstore indexes
- Implement data warehouse storage
  • 1. Configure filegroups and partitions
  • 2. Plan storage requirements
- Design and implement dimension and fact tables
  • 1. Design shared and conformed dimensions
  • 2. Implement slowly changing dimensions
  • 3. Design and implement partitioned tables and views
Topic 2: Extract, transform, and load data40–45%- Design and implement ETL control flow
  • 1. Implement error handling and logging
  • 2. Use SSIS containers and tasks
- Implement incremental data loads
  • 1. Detect changed data
  • 2. Use change data capture and temporal tables
- Deploy and configure SSIS solutions
  • 1. Configure SSIS catalog and environments
  • 2. Deploy SSIS projects and packages
- Design and implement ETL data flow
  • 1. Apply transformations and lookups
  • 2. Use SSIS data sources and destinations
Topic 3: Build data quality solutions15–20%- Implement Master Data Services (MDS)
  • 1. Use MDS tools and web application
  • 2. Create and manage MDS models and entities
- Implement Data Quality Services (DQS)
  • 1. Build and manage DQS knowledge bases
  • 2. Perform data cleansing and matching
- Maintain data quality
  • 1. Monitor data consistency
  • 2. Implement data validation rules

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