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SSAS : Microsoft SQL Server Analysis Services

With this course, you will be able to become an expert in employing both engines within a company’s infrastructure. Analysis Services is composed of two powerful applications – VertiPaq and Data Mining for multidimensional cubes, as well as xVelocity for Tabular Data Models. It provides enterprise-level semantic data modeling abilities to construct business intelligence systems such as Power BI, Excel Reporting Services and other information visualization tools that can make your organization even more successful!

Included In This Course

Included In This Course

Total Hours
8  Training Hours
SSAS : Microsoft SQL Server Analysis Services
50 On-demand Videos
Closed Caption

Closed Captions

Course Topics
9  Topics
Prep Questions
75 Prep Questions
SSAS : Microsoft SQL Server Analysis Services

Certificate of Completion

Course Description

Unlock the power of data analytics with our comprehensive course on Microsoft SQL Server Analysis Services, SSAS. Whether you’re new to SSAS or looking to deepen your understanding, this course covers everything from the basics to advanced topics. Learn what SSAS means in the context of business intelligence, master the art of creating SSAS cubes, and explore the SSAS tabular model to make data-driven decisions.

SSAS Course Learning Topics

Module 1 – Introduction to Business Intelligence and Data Modeling

Kickstart your journey into the world of business intelligence and data modeling with Module 1. This module serves as an introduction to what SSAS is and how it fits into the Microsoft Business Intelligence Platform. You’ll explore key concepts like data warehouses and data models, setting the stage for the more advanced topics to come.

Module 2 – Multidimensional Databases

Module 2 dives into the core of SSAS by introducing you to multidimensional databases. Learn how to secure your data with cube security and get hands-on experience in creating and configuring an SSAS cube. This module also covers essential topics like data sources and data source views, rounding off with adding a dimension to a cube.

Module 3 – Cubes and Dimensions

In Module 3, you’ll delve deeper into the world of SSAS cubes and dimensions. Learn about attribute hierarchies, relationships, and how to sort and group attributes effectively. The module also covers the concept of slowly changing dimensions, a crucial aspect of SQL SSAS.

Module 4 – Measures and Measure Groups

Module 4 focuses on the quantitative aspects of SSAS, covering measures and measure groups. Learn how to define measures, set up measure groups, and understand their relationships. You’ll also explore different storage options for measure groups, all within the SQL SSAS environment.

Module 5 – Introduction to MDX

Get acquainted with the Multidimensional Expressions (MDX) language in Module 5. This module covers MDX fundamentals and teaches you how to add calculations to an SSAS cube. You’ll also learn how to query a cube using MDX, a key skill in SSAS SQL.

Module 6 – Customizing Cube Functionality

Module 6 empowers you to customize your SSAS cubes to meet specific business needs. Learn how to set up Key Performance Indicators (KPIs), create actions, and add perspectives and translations to your cubes, enhancing their functionality and usability.

Module 7 – Tabular Data Models

Module 7 introduces you to the SSAS tabular model, an alternative to the traditional multidimensional model. Learn how to create a tabular data model, configure relationships and attributes, and set up your data model for an enterprise BI solution.

Module 8 – Data Analysis Expressions (DAX)

Dive into the world of Data Analysis Expressions (DAX) in Module 8. This module covers DAX fundamentals and advanced topics like calculated columns, relationships, measures, and time intelligence. You’ll also explore KPIs and parent-child hierarchies within the SSAS tabular model.

Module 9 – Data Mining

Wrap up your SSAS training with Module 9, which provides an overview of data mining in SQL Server SSAS. Learn how to create custom data mining solutions, validate a data mining model, and consume the model for actionable insights.

By the end of this course, you’ll be well-equipped to leverage Microsoft SSAS for your business intelligence needs, from creating SSAS cubes to mastering the SSAS tabular model. Join us to become an SSAS expert today!

Who Is This SSAS Training For?

This course is ideal for a wide range of professionals and enthusiasts who are interested in diving into the world of data analytics and business intelligence. Here are some groups who would particularly benefit:

  1. Data Analysts: Those who are already familiar with data analysis but want to specialize in SSAS for more advanced, multidimensional analytics.
  2. Business Intelligence Professionals: Individuals who are in the BI field and want to expand their skill set to include SSAS for more robust data modeling and analytics.
  3. Database Administrators: DBAs who are looking to add SSAS to their toolkit for better data management and analytics can greatly benefit from this course.
  4. SQL Developers: Those who have a good grasp of SQL and want to move into the specialized area of SQL Server Analysis Services.
  5. IT Professionals: Anyone in IT who wants to understand how SSAS can be used for better data analytics in their organization.
  6. Consultants: Business and data consultants who need to understand SSAS to provide comprehensive solutions to their clients.
  7. Students and Academics: Those studying computer science, data science, or a related field who want to gain a practical, in-depth understanding of SSAS.
  8. Career Changers: Individuals looking to transition into a data-centric role would find this course a valuable stepping stone.
  9. Data Enthusiasts: Even if you’re not a professional but have a keen interest in data analytics, this course will provide you with the skills you need to understand and use SSAS effectively.
  10. Enterprise Decision-Makers: Managers and executives who want to understand how SSAS can help in data-driven decision-making will also find this course useful.

By the end of this course, participants will have a solid understanding of what SSAS is, how to create SSAS cubes, and how to use the SSAS tabular model for business intelligence and data analytics. This makes the course a valuable resource for anyone looking to upskill or break into the field of data analytics.

Salary & Job Opportunities For Those Working With SSAS

Below is a sample salary table that outlines the potential earnings for professionals who work with SQL Server Analysis Services (SSAS). Please note that these figures are approximate and can vary based on factors such as experience, location, and the specific responsibilities of the role. All figures are in U.S. dollars and are based on annual earnings.

Job TitleEntry-Level SalaryMid-Level SalarySenior-Level Salary
SSAS Developer$70,000 – $85,000$86,000 – $105,000$106,000 – $130,000
Data Analyst (SSAS Specialization)$60,000 – $75,000$76,000 – $95,000$96,000 – $115,000
Business Intelligence Analyst$65,000 – $80,000$81,000 – $100,000$101,000 – $125,000
Database Administrator (DBA)$72,000 – $88,000$89,000 – $110,000$111,000 – $140,000
BI Developer (SSAS Focus)$75,000 – $90,000$91,000 – $110,000$111,000 – $135,000
Data Architect$90,000 – $110,000$111,000 – $135,000$136,000 – $160,000
Data Engineer (SSAS Expertise)$85,000 – $100,000$101,000 – $120,000$121,000 – $145,000
Data Scientist (SSAS Knowledge)$95,000 – $115,000$116,000 – $140,000$141,000 – $170,000
IT Manager (SSAS Experience)$100,000 – $120,000$121,000 – $145,000$146,000 – $175,000
Consultant (SSAS Specialization)$80,000 – $100,000$101,000 – $125,000$126,000 – $155,000

Additional Benefits:

  • Health Insurance
  • Retirement Plans
  • Performance Bonuses
  • Skill Development Programs
  • Work-from-Home Options

It’s important to note that these are general estimates and actual salaries can vary based on a multitude of factors including the company, the cost of living in the location, and additional skills that complement SSAS expertise.

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Key Term Knowledge Base: Key Terms Related to Microsoft SQL Server 2019 Analysis Services (SSAS)

Understanding the key terms related to Microsoft SQL Server 2019 Analysis Services (SSAS) is crucial for professionals working in fields like business intelligence, data analysis, and database management. This knowledge base will help in comprehending the functionalities, features, and technical aspects of SSAS, enabling better utilization of this powerful tool for data analytics and business intelligence.

SSASSQL Server Analysis Services, a tool for online analytical processing and data mining in SQL Server.
Business Intelligence (BI)Technologies, applications, and practices for collecting, integrating, analyzing, and presenting business information.
Data ModelingThe process of creating a data model for the data to be stored in a database.
Multidimensional DatabaseA type of database that is optimized for data warehouse and online analytical processing (OLAP) applications.
CubeA data structure in SSAS that allows data to be modeled and analyzed in multiple dimensions.
DimensionA structure that categorizes data in order to enable users to answer business questions.
MDX (Multidimensional Expressions)A query language for OLAP databases, similar to SQL.
Tabular Data ModelA type of data model in SSAS that uses relational modeling techniques.
Data MiningThe practice of examining large databases to generate new information.
SQL ServerA relational database management system developed by Microsoft.
OLAP (Online Analytical Processing)An approach to quickly answer multi-dimensional analytical queries.
Data WarehouseA system used for reporting and data analysis, storing historical data.
ETL (Extract, Transform, Load)A process in database usage and data warehousing.
DAX (Data Analysis Expressions)A collection of functions, operators, and constants for data analysis and calculations.
QueryA request for data or information from a database.
Relational DatabaseA database structured to recognize relations among stored items of information.
Data MartA subset of a data warehouse focused on a specific business line or team.
Star SchemaA type of database schema that is common in data warehousing.
Snowflake SchemaA more complex version of a star schema used in a data warehouse.
KPI (Key Performance Indicator)A measurable value that demonstrates how effectively a company is achieving key business objectives.
PartitioningThe process of dividing a database into multiple pieces for performance or organization reasons.
AggregationA process in OLAP where summary data is computed and stored.
HierarchiesStructures in data that represent relationships where one item contains other items.
MeasureA property on which calculations (like sum, count, average) can be made in a cube.
Data SourceThe location and method of connection to the data that is to be processed and analyzed.
Analysis Services Scripting Language (ASSL)The XML language used to define objects in SSAS.
SQL Server Management Studio (SSMS)An integrated environment for managing SQL Server infrastructure.
Power BIA business analytics service by Microsoft for interactive visualizations and business intelligence capabilities.
Data CleansingThe process of detecting and correcting (or removing) corrupt or inaccurate records from a database.
Dimensional ModelingA data modeling technique in data warehouse design, optimized for querying and reporting.
Fact TableA table in a star schema of a data warehouse that contains measured quantities.

Frequently Asked Questions About Microsoft SQL Server Analysis Services (SSAS)

What is SSAS and Why is it Important for Business Intelligence?

SSAS stands for SQL Server Analysis Services, a part of Microsoft’s SQL Server suite. It is used for advanced analytics and business intelligence. SSAS allows you to create multidimensional cubes and tabular data models, enabling fast and efficient querying and analysis of large datasets. It plays a crucial role in helping businesses make data-driven decisions by providing tools for data modeling, analysis, and visualization.

What is the Difference Between SSAS Multidimensional and SSAS Tabular?

SSAS offers two types of data models: Multidimensional and Tabular. The Multidimensional model is more traditional and is optimized for complex queries and OLAP (Online Analytical Processing). The Tabular model is newer and is generally easier to set up, offering faster performance for simpler queries. Both have their own use-cases, and the choice between the two often depends on the specific needs of a project.

How Does SSAS Integrate with Other Microsoft Tools?

ISSAS integrates seamlessly with other Microsoft tools like SQL Server, Excel, and Power BI. You can import data from SQL Server into SSAS to create cubes or tabular models. These can then be easily accessed and visualized using Excel or Power BI, providing a comprehensive business intelligence solution within the Microsoft ecosystem.

Is Learning MDX Necessary for Working with SSAS?

MDX, or Multidimensional Expressions, is a query language for OLAP databases like SSAS. While it’s not strictly necessary to know MDX to work with SSAS, having a good grasp of MDX can be beneficial, especially if you’re working with the Multidimensional model. It allows you to write custom queries and calculations, providing more flexibility in your data analysis.

What are the Career Opportunities for Professionals Skilled in SSAS?

Professionals with expertise in SSAS have a range of career opportunities available to them, including roles like SSAS Developer, Business Intelligence Analyst, Data Architect, and Database Administrator. These roles are in high demand across various industries, and proficiency in SSAS is often associated with higher earning potential.

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Course Outline

Microsoft SQL Server 2019 Analysis Services (SSAS) Course Content

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

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

Module 3 - Cubes and Dimensions

  •    3.1 Module 3 Introduction

  •    3.2 Dimensions

  •    3.3 Attribute Hierarchies and Relationships

  •    3.4 Sorting and Grouping Attributes

  •    3.5 Slowly Changing Dimensions

Module 4 - Measures and Measure Groups

  •    4.1 Module 4 Introduction

  •    4.2 Measures

  •    4.3 Measure Groups and Relationships

  •    4.4 Measure Group Storage

Module 5 - Introduction to MDX

  •    5.1 Module 5 Introduction

  •    5.2 MDX Fundamentals

  •    5.3 Adding Calculations to a Cube

  •    5.4 Querying a cube using MDX

Module 6 - Customizing Cube Functionality

  •    6.1 Module 6 Introduction

  •    6.2 Key Performance Indicators

  •    6.3 Actions

  •    6.4 Perspectives

  •    6.5 Translations

Module 7 - Tabular Data Models

  •    7.1 Module 7 Introduction

  •    7.2 Introduction to Tabular Data Models

  •    7.3 Creating a Tabular Data Model

  •    7.4 Configure Relationships and Attributes

  •    7.5 Configuring Data Model for an Enterprise BI Solution

Module 8 - Data Analysis Expressions (DAX)

  •    8.1 Module 8 Introduction

  •    8.2 DAX Fundamentals

  •    8.3 Calculated Columns

  •    8.4 Relationships

  •    8.5 Measures

  •    8.6 Time Intelligence

  •    8.7 KPI

  •    8.8 Parent - Child Hierarchies

Module 9 - Data Mining

  •    9.1 Module 9 Introduction

  •    9.2 Overview of Data Mining

  •    9.3 Custom Data Mining Solutions

  •    9.4 Validating a Data Mining Model

  •    9.5 Consuming a Data Mining Model

  •    9.6 Course Wrap Up

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Your Training Instructor

James Ring-Howell

James Ring-Howell

Microsoft Certified Trainer | Microsoft Certified Developer | Database Expert

James is a full-stack developer with over 40 years of experience. He has developed applications across all major industries and for Fortune 100 companies as well as local small businesses. James has also been teaching technology courses for over 20 years. In addition to his extensive background in technology, he has also worked as a professional opera singer.

SSAS : Microsoft SQL Server Analysis Services



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SSAS : Microsoft SQL Server Analysis Services

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SSAS : Microsoft SQL Server Analysis Services
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