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Microsoft SQL Server 2019 Analysis Services (SSAS)

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Certificate

Dedicated Tutors

50 Videos
8.56 Hours
75 Test Questions

Microsoft SQL Server 2019 Analysis Services (SSAS)

Course Highlights

Closed Caption

Certificate

Dedicated Tutors

8.56 Hours
50 Videos

Microsoft SQL Server 2019 Analysis Services (SSAS)

Course Description

8.56 Hours

50 Videos

Microsoft SQL Server 2019 Analysis Services (SSAS)

The Microsoft SQL Server 2019 Analysis Services (SSAS) course provides a deep dive into the powerful data analysis and business intelligence capabilities of SQL Server 2019. Designed for data analysts, BI developers, and IT professionals, this course covers the essentials of building and managing multidimensional and tabular models using SSAS. Participants will learn how to create complex data models, design efficient data cubes, and deploy solutions that drive insightful business decisions.

Key Features:

  • Multidimensional Model Design: Learn to design and deploy multidimensional models with OLAP cubes, including defining dimensions, measures, and hierarchies to analyze data from various perspectives.
  • Tabular Model Development: Explore tabular data models to build scalable and high-performance solutions, utilizing data analysis expressions (DAX) to create complex calculations and business logic.
  • Data Processing and Management: Understand how to process, manage, and refresh data within SSAS models, including scheduling data updates and handling data source changes.
  • Performance Optimization: Discover techniques for optimizing query performance and improving the efficiency of SSAS models through indexing, partitioning, and caching strategies.
  • Security and Permissions: Learn how to implement security measures to protect sensitive data, including configuring role-based security and managing permissions for users and groups.
  • Integration with Power BI: Gain insights into integrating SSAS models with Power BI to enhance data visualization and reporting capabilities, and leverage SSAS as a data source for interactive dashboards.
  • Data Analysis Expressions (DAX): Master DAX language to create advanced calculations, measures, and KPIs, enabling more sophisticated data analysis and reporting.
  • Troubleshooting and Maintenance: Develop skills to troubleshoot common issues, monitor SSAS performance, and perform routine maintenance to ensure reliable and accurate data analysis.

This course is tailored for professionals looking to harness the full potential of SSAS for sophisticated data analysis and business intelligence, providing them with the tools to deliver actionable insights and support data-driven decision-making.

Course Highlights

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Course Syllabus

Chapter One:

Module 1 – Introduction to Business Intelligence and Data Modeling

  • 1.1 Course Introduction
  • 1.2 Module 1 Introduction
  • 1.3 Introduction to Business Intelligence
  • 1.4 The Microsoft Business Intelligence Platform
  • 1.5 Exploring a Data Warehouse
  • 1.6 Exploring a Data Model
Chapter Two:

Module 2 – Multidimensional Databases

  •  2.1 Module 2 Introduction
  •  2.2 Introduction to Multidimensional Analysis
  •  2.3 Overview of Cube Security
  •  2.4 Creating and Configuring a Cube
  •  2.5 Data Sources
  •  2.6 Data Source Views
  •  2.7 Adding a Dimension to a Cube
Chapter Three:

Module 3 – Cubes and Dimensions

  • 1 Module 3 Introduction
  • 2 Dimensions
  • 3 Attribute Hierarchies and Relationships
  • 4 Sorting and Grouping Attributes
  • 5 Slowly Changing Dimensions
Chapter Four:

Module 4 – Measures and Measure Groups

  • 1 Module 4 Introduction
  • 2 Measures
  • 3 Measure Groups and Relationships
  • 4 Measure Group Storage
Chapter Five:

Module 5 – Introduction to MDX

  • 1 Module 5 Introduction
  • 2 MDX Fundamentals
  • 3 Adding Calculations to a Cube
  • 4 Querying a cube using MDX
Chapter Six:

Module 6 – Customizing Cube Functionality

  • 1 Module 6 Introduction
  • 2 Key Performance Indicators
  • 3 Actions
  • 4 Perspectives
  • 5 Translations
Chapter Seven:

Module 7 – Tabular Data Models

  • 1 Module 7 Introduction
  • 2 Introduction to Tabular Data Models
  • 3 Creating a Tabular Data Model
  • 4 Configure Relationships and Attributes
  • 5 Configuring Data Model for an Enterprise BI Solution
Chapter Eight:

Module 8 – Data Analysis Expressions (DAX)

  • 1 Module 8 Introduction
  • 2 DAX Fundamentals
  • 3 Calculated Columns
  • 4 Relationships
  • 5 Measures
  • 6 Time Intelligence
  • 7 KPI
  • 8 Parent – Child Hierarchies
Chapter Nine:

Module 9 – Data Mining

  • 1 Module 9 Introduction
  • 2 Overview of Data Mining
  • 3 Custom Data Mining Solutions
  • 4 Validating a Data Mining Model
  • 5 Consuming a Data Mining Model
  • 6 Course Wrap Up

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course Syllabus

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$53.60

Frequently Asked Questions

Instructional methods, course requirements, and learning technologies can vary significantly from one online program to the next, but the vast bulk of them use a learning management system (LMS) to deliver lectures and materials, monitor student progress, assess comprehension, and accept student work. LMS providers design these platforms to accommodate a multitude of instructor needs and preferences.

Online education may seem relatively new, but years of research suggests it can be just as effective as traditional coursework, and often more so. According to a U.S. Department of Education analysis of more than 1,000 learning studies, online students tend to outperform classroom-based students across most disciplines and demographics. Another major review published the same year found that online students had the advantage 70 percent of the time, a gap authors projected would only widen as programs and technologies evolve.

All new learning innovations are met with some degree of scrutiny, but skepticism subsides as methods become more mainstream. Such is the case for online learning. Studies indicate employers who are familiar with online degrees tend to view them more favorably, and more employers are acquainted with them than ever before. The majority of colleges now offer online degrees, including most public, not-for-profit, and Ivy League universities. Online learning is also increasingly prevalent in the workplace as more companies invest in web-based employee training and development programs.

The concern that online students cheat more than traditional students is perhaps misplaced. When researchers at Marshall University conducted a study to measure the prevalence of cheating in online and classroom-based courses, they concluded, “Somewhat surprisingly, the results showed higher rates of academic dishonesty in live courses.” The authors suggest the social familiarity of students in a classroom setting may lessen their sense of moral obligation.

Choosing the right course takes time and careful research no matter how one intends to study. Learning styles, goals, and programs always vary, but students considering online courses must consider technical skills, ability to self-motivate, and other factors specific to the medium. Online course demos and trials can also be helpful.
Our platform is typically designed to be as user-friendly as possible: intuitive controls, clear instructions, and tutorials guide students through new tasks. However, students still need basic computer skills to access and navigate these programs. These skills include: using a keyboard and a mouse; running computer programs; using the Internet; sending and receiving email; using word processing programs; and using forums and other collaborative tools. Most online programs publish such requirements on their websites. If not, an admissions adviser can help.

Frequently Asked Questions

Instructional methods, course requirements, and learning technologies can vary significantly from one online program to the next, but the vast bulk of them use a learning management system (LMS) to deliver lectures and materials, monitor student progress, assess comprehension, and accept student work. LMS providers design these platforms to accommodate a multitude of instructor needs and preferences.

Online education may seem relatively new, but years of research suggests it can be just as effective as traditional coursework, and often more so. According to a U.S. Department of Education analysis of more than 1,000 learning studies, online students tend to outperform classroom-based students across most disciplines and demographics. Another major review published the same year found that online students had the advantage 70 percent of the time, a gap authors projected would only widen as programs and technologies evolve.

All new learning innovations are met with some degree of scrutiny, but skepticism subsides as methods become more mainstream. Such is the case for online learning. Studies indicate employers who are familiar with online degrees tend to view them more favorably, and more employers are acquainted with them than ever before. The majority of colleges now offer online degrees, including most public, not-for-profit, and Ivy League universities. Online learning is also increasingly prevalent in the workplace as more companies invest in web-based employee training and development programs.

The concern that online students cheat more than traditional students is perhaps misplaced. When researchers at Marshall University conducted a study to measure the prevalence of cheating in online and classroom-based courses, they concluded, “Somewhat surprisingly, the results showed higher rates of academic dishonesty in live courses.” The authors suggest the social familiarity of students in a classroom setting may lessen their sense of moral obligation.

Choosing the right course takes time and careful research no matter how one intends to study. Learning styles, goals, and programs always vary, but students considering online courses must consider technical skills, ability to self-motivate, and other factors specific to the medium. Online course demos and trials can also be helpful.
Our platform is typically designed to be as user-friendly as possible: intuitive controls, clear instructions, and tutorials guide students through new tasks. However, students still need basic computer skills to access and navigate these programs. These skills include: using a keyboard and a mouse; running computer programs; using the Internet; sending and receiving email; using word processing programs; and using forums and other collaborative tools. Most online programs publish such requirements on their websites. If not, an admissions adviser can help.

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Description

Microsoft SQL Server 2019 Analysis Services (SSAS)

The Microsoft SQL Server 2019 Analysis Services (SSAS) course provides a deep dive into the powerful data analysis and business intelligence capabilities of SQL Server 2019. Designed for data analysts, BI developers, and IT professionals, this course covers the essentials of building and managing multidimensional and tabular models using SSAS. Participants will learn how to create complex data models, design efficient data cubes, and deploy solutions that drive insightful business decisions.

Key Features:

  • Multidimensional Model Design: Learn to design and deploy multidimensional models with OLAP cubes, including defining dimensions, measures, and hierarchies to analyze data from various perspectives.
  • Tabular Model Development: Explore tabular data models to build scalable and high-performance solutions, utilizing data analysis expressions (DAX) to create complex calculations and business logic.
  • Data Processing and Management: Understand how to process, manage, and refresh data within SSAS models, including scheduling data updates and handling data source changes.
  • Performance Optimization: Discover techniques for optimizing query performance and improving the efficiency of SSAS models through indexing, partitioning, and caching strategies.
  • Security and Permissions: Learn how to implement security measures to protect sensitive data, including configuring role-based security and managing permissions for users and groups.
  • Integration with Power BI: Gain insights into integrating SSAS models with Power BI to enhance data visualization and reporting capabilities, and leverage SSAS as a data source for interactive dashboards.
  • Data Analysis Expressions (DAX): Master DAX language to create advanced calculations, measures, and KPIs, enabling more sophisticated data analysis and reporting.
  • Troubleshooting and Maintenance: Develop skills to troubleshoot common issues, monitor SSAS performance, and perform routine maintenance to ensure reliable and accurate data analysis.

This course is tailored for professionals looking to harness the full potential of SSAS for sophisticated data analysis and business intelligence, providing them with the tools to deliver actionable insights and support data-driven decision-making.

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