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Microsoft Developing SQL Data Models : 070-768

070-768

Exam Code: 070-768

Exam Name: Developing SQL Data Models

Updated: Jul 25, 2026

Q&A Number: 70 Q&As

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070-768 Online Test Engine

Microsoft 070-768 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Monitor Processing And Query Performance, Resolve Performance Issues, Configure Usability Limits, Optimize And Manage Model Design
Topic 2
  • Select An Appropriate Dimension Model, Such As Fact, Parent-Child, Roleplaying, Reference, Data Mining, Many-To-Many, And Slowly Changing Dimension
Topic 3
  • Implement Measures And Measure Groups In A Cube
  • Create Formulas By Using The DAX Language
  • Implement Custom MDX Solutions
Topic 4
  • Use Directquery With Oracle, Teradata, Excel, And Pivottables; Convert In-Memory Queries To Directquery
Topic 5
  • Create A Multidimensional Database By Using Microsoft SQL Server Analysis Services (SSAS)
Topic 6
  • Import From Microsoft Powerpivot; Select A Deployment Option, Including Processing Option, Transactional Deployment, And Query Mode
Topic 7
  • Process Structure, And Process Clear Structure Processing Methods; Configure Parallel, Sequential, And Writeback Processing Settings
Topic 8
  • Monitor Performance And Analyze Query Plans By Using Extended Events And Profiler, Identify Bottlenecks In SSAS Queries
Topic 9
  • Configure Partition Processing; Configure Dimension Processing; Use Process Default, Process Full, Process Clear, Process Data, Process Add, Process Update, Process Index
Topic 10
  • Create Custom MDX Or Logical Solutions For Pre-Prepared Case Tasks Or Business Rules, Define A SCOPE Statement
Topic 11
  • Configure Tabular Model Storage And Data Refresh, Configure Refresh Interval Settings, Configure User Security And Permissions, Configure Row-Level Security

Reference: https://www.microsoft.com/en-us/learning/exam-70-768.aspx

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Languages: English

This exam is intended for business intelligence (BI) developers who focus on creating BI solutions that require implementing multidimensional data models, implementing and maintaining OLAP cubes, and implementing tabular data models.

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