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Microsoft 070-768: Developing SQL Data Models exam is a certification exam designed for professionals who are interested in acquiring the knowledge and skills required to develop SQL data models. 070-768 exam helps the candidates to validate their knowledge and skills in designing, implementing, and maintaining SQL data models. 070-768 exam is ideal for database developers, data analysts, and data architects who work with SQL Server.
Passing the Microsoft 070-768 exam requires a significant amount of preparation and studying. Candidates are expected to have in-depth knowledge of SQL Server, data modeling principles, and SSAS. There are various study materials available online, including official Microsoft resources and third-party study guides. Candidates can also enroll in training courses to help prepare for the exam.
Reference: https://www.microsoft.com/en-us/learning/exam-70-768.aspx
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The Developing SQL Data Models certification exam is intended for professionals who work with SQL Server and are involved in the development of data models, including data architects, database developers, and business intelligence developers. It is also suitable for professionals who are looking to advance their careers in data management and analytics.
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The Microsoft 070-768 exam tests the candidates' knowledge of the fundamental concepts of data modeling, including multidimensional and tabular models, data processing, and data mining. It also evaluates their understanding of the techniques and tools used to design, develop, and deploy SQL data models that meet business requirements.
Microsoft 070-768 Exam Syllabus Topics:
| Section | Objectives |
| Develop and deploy SQL Server Analysis Services (SSAS) models | - Create tabular models
- Create multidimensional models
- Configure partitions and storage modes
|
| Implement DAX calculations and expressions | - Use DAX functions for filtering and time intelligence
- Create calculated columns and measures
|
| Implement data integrity and performance optimization | - Indexing and query optimization
- Data refresh and processing strategies
|
| Design and implement data models | - Implement tables, relationships, and constraints
- Design conceptual, logical, and physical data models
- Normalize and optimize data structures
|