Developing SQL 2016 Data Models (SSAS)

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About Course

The Developing SQL 2016 Data Models (SSAS) course is designed to provide learners with a comprehensive understanding and practical skill set for implementing data models using Microsoft SQL Server Analysis Services (MS SSAS). This course covers various aspects of both multidimensional and tabular data models, diving into the creation and management of cubes, dimensions, and measures. Learners will also explore the essentials of the Multidimensional Expressions (MDX) language and the Data Analysis Expressions (DAX) language for more complex data manipulation and analysis.Throughout the course, students will gain practical experience with MS SSAS through a series of labs that reinforce the lessons, enabling them to configure dimensions, measure groups, and implement security within their data models. Additionally, learners will delve into predictive analytics with data mining, a key feature of MS SQL Server Analysis Services. By the end of the course, participants will have the skills to build robust, efficient data models that are essential for enterprise-level business intelligence solutions.

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What Will You Learn?

  • Understand the fundamentals of business intelligence and the Microsoft BI platform.
  • Learn to create and manage multidimensional structures such as data sources, data source views, and cubes.
  • Configure dimensions, attributes, and measure groups for accurate data analysis.
  • Implement cube security to protect sensitive business information.
  • Develop proficiency in Multidimensional Expressions (MDX) for adding calculations and querying cubes.
  • Customize cubes with advanced features like key performance indicators (KPIs), actions, perspectives, and translations.
  • Construct and deploy tabular data models using Analysis Services to enhance enterprise BI solutions.
  • Apply Data Analysis Expressions (DAX) to create calculated columns and measures within tabular models.
  • Perform predictive analysis by employing data mining techniques and validate the accuracy of data mining models.
  • Integrate and consume data mining models in business scenarios for informed decision-making.
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