To pass the Microsoft 070-768 certification exam, candidates must demonstrate proficiency in a range of topics, including designing and implementing dimensions, fact tables, and measures; creating and deploying SSAS tabular models; developing and deploying Power BI reports; and optimizing data models for performance. 070-768 exam is designed to test the candidate's ability to work with different data sources, combine data from multiple sources, and create complex data models that meet the needs of business users. Passing the Microsoft 070-768 certification exam can help professionals demonstrate their expertise in data modeling and analysis, which can lead to new job opportunities and career advancement.
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Microsoft 70-768 Exam Reference
Microsoft 070-768 exam is designed for professionals who want to become certified in developing SQL data models. 070-768 exam is intended for individuals who have a solid understanding of SQL Server and its related technologies. The primary goal of 070-768 exam is to test the candidate’s ability to design and implement SQL data models that meet business requirements.
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The 070-768 exam focuses on testing the candidate's ability to design, develop, and deploy SQL data models in a variety of scenarios. These scenarios include building both multidimensional and tabular data models, implementing measures and metrics, and creating different types of visualizations to showcase the data in the most effective way possible.
Microsoft 070-768 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement DAX calculations and expressions | - Create calculated columns and measures - Use DAX functions for filtering and time intelligence |
| Develop and deploy SQL Server Analysis Services (SSAS) models | - Create multidimensional models - Create tabular models - Configure partitions and storage modes |
| Design and implement data models | - Implement tables, relationships, and constraints - Normalize and optimize data structures - Design conceptual, logical, and physical data models |
| Implement data integrity and performance optimization | - Data refresh and processing strategies - Indexing and query optimization |






