Developing a Multidimensional Data Model

开始时间: 04/22/2022 持续时间: 6 weeks

所在平台: EdxArchive 课程类别: 其他类别 大学或机构: Microsoft 授课老师： Chris Randall Peter Myers

课程主页: https://www.edx.org/archive/developing-multidimensional-data-model-microsoft-dat224x-0

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课程详情

If you have large volumes of data and you need to deliver intuitive, interactive, and high-performance access to it, don’t miss this course!

Whether you're new to SQL Server 2016 Analysis Services or you’re experienced with previous versions, join us for a look at this powerful technology.

Learn how to design dimensions that enable you to browse data with hierarchy memberships. Then explore ways to assemble these dimensions in order to analyze measures in cubes.

You’ll get details on how to enhance your cubes with business logic; creating calculated members, named sets, scoped assignments, and key performance indicators (KPIs) with MDX—the language of multidimensional models.

Compare tabular and multidimensional Analysis Services models, so you can determine which is best for your project. Plus, find out how to manage and optimize multidimensional databases as you explore storage, processing, security, and deployment. Watch instructor demonstrations, and then roll up your sleeves to apply the lessons yourself with sample data in comprehensive, hands-on exercises.

By the end of the course, you'll have designed, developed, and deployed a multidimensional model, ready to deliver high-performance business user experiences. Register today for this practical SQL Server 2016 Analysis Services course.

Note: To complete the hands-on elements in this course, you will require an Azure subscription. You can sign up for a free Azure trial subscription (a valid credit card is required for verification, but you will not be charged for Azure services). Note that the free trial is not available in all regions. It is possible to complete the course and earn a certificate without completing the hands-on practices.

课程大纲

• How to develop multidimensional models
• Connecting to source data
• Developing dimensions and cubes
• Enhancing cubes with business logic
• Managing and optimizing multidimensional databases
• Comparing tabular and multidimensional models

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