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SQL Server 70-768: Developing SQL Data Models LiveLessons (Video Training)

SQL Server 70-768: Developing SQL Data Models LiveLessons (Video Training)

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  • Copyright 2018
  • Edition: 1st
  • Online Video
  • ISBN-10: 0-13-484088-7
  • ISBN-13: 978-0-13-484088-8

6+ Hours of Video Instruction

Prepare for Microsoft Exam 70-768: Developing SQL Data Models and develop practical Business Intelligence (BI) skills with more than 6 hours of video instruction and hands-on demonstrations.

SQL Server Analysis Services (SSAS) provides a robust semantic environment for modeling data in support of analytic and ad hoc reporting needs. With each release of SQL Server, SSAS functionality is enhanced, with tabular models in particular becoming more capable and fully featured.

In this video, Scot Reagin couples discussion with demonstration to give you not just an understanding of the functional differences between multidimensional and tabular models, but also the context to understand where and why each should be implemented.

In addition to a comprehensive discussion of design and implementation topics, Scot covers techniques for developing queries using multidimensional and data analysis expressions, optimizing processing and query performance, and configuring and maintaining SSAS.

Skill Level

  • Intermediate

Learn How To
  • Design a multidimensional semantic model
  • Design a tabular semantic model
  • Develop queries using MDX and DAX
  • Configure and maintain SSAS

Who Should Take This Course
  • IT professionals responsible for designing, developing, maintaining, or administering SQL Server Analysis Services (SSAS)
  • BI developers pursuing Microsoft Certification

Course Requirements
  • Basic understanding of relational databases and SQL queries
  • Familiarity with Microsoft SQL Server client tools

Lesson Descriptions

Lesson 1,  Designing a Multidimensional Semantic Model, covers building a multidimensional semantic model—a Cube. Create the fundamental components for the model, dimensions, and measures as a project and deploy this to Analysis Service.

Lesson 2, Designing a Tabular Semantic Model, demonstrates how to build and deploy tabular models while exploring security and refresh options.

Lesson 3, Developing Queries Using MDX and DAX, covers developing queries and expressions using MDX and DAX. Understanding these query languages is essential to optimizing Analysis Services models—whether multidimensional or tabular.

Lesson 4, Configuring and Maintaining SSAS, looks at ways to monitor and configure Analysis Services for best performance.

About Pearson Video Training

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.

Sample Content

Table of Contents


Lesson 1: Designing a Multidimensional Semantic Model
1.1: Create a multidimensional database
1.2: Choose a dimensional model
1.3: Define attribute relationships
1.4: Create measures and measure groups
1.5: Define aggregation functions

Lesson 2: Designing a Tabular Semantic Model
2.1: Create a tabular model
2.2: Deploy and process a tabular model
2.3: Configure tabular model storage and refresh settings
2.4: Configure user and data security

Lesson 3: Developing Queries Using MDX and DAX
3.1: Understand MDX fundamentals
3.2: Use MDX calculated members and sets
3.3: Use MDX functions
3.4: Use the SCOPE statement
3.5: Create MDX solutions
3.6: Use the EVALUATE and CALCULATE functions
3.7: Create calculated measures
3.8: Perform data analysis with DAX

Lesson 4: Configuring and Maintaining SSAS
4.1: Plan and deploy SSAS
4.2: Monitor performance
4.3: Identify bottlenecks and improve performance
4.4: Configure limits and model design
4.5: Configure partition processing
4.6: Configure dimension processing
4.7: Create KPIs in cubes
4.8: Create KPIs in tabular models
4.9: Create actions
4.10: Create translations



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