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What you learn
- How to create a new tabular model project at the 1400 compatibility level in Visual Studio with SSDT.
- How to import data from a relational database into a tabular model project workspace database.
- How to create and manage relationships between tables in the model.
- How to create calculated columns, measures, and Key Performance Indicators that help users analyze critical business metrics.
- How to create and manage perspectives and hierarchies that help users more easily browse model data by providing business and application-specific viewpoints.
- How to create partitions that divide table data into smaller logical parts that can be processed independent from other partitions.
- How to secure model objects and data by creating roles with user members.
- How to deploy a tabular model to an Azure Analysis Services server or SQL Server 2017 Analysis Services server by using SSDT.
To complete this tutorial, you need:
- An Azure Analysis Services server or a SQL Server 2017 Analysis Services server in Tabular mode. Sign up for a free Azure Analysis Services trial and create a server or download a free SQL Server 2017 Developer Edition.
- An Azure SQL Data Warehouse with the sample AdventureWorksDW database, or an on-premises SQL Server Data Warehouse with an AdventureWorksDW sample database. When installing an AdventureWorksDW database to an on-premises SQL Server Data Warehouse, use the sample datbase version that corresponds with your server version.
Important: If you install the sample database to an on-premises SQL Server Data Warehouse, and deploy your model to an Azure Analysis Services server, an On-premises data gateway is required.
- The latest version of SQL Server Data Tools (SSDT). Or, if you already have Visual Studio 2017, you can download and install Microsoft Analysis Services Projects (VSIX) package. For this tutorial, references to SSDT and Visual Studio are synonymous.
- The latest version of SQL Server Management Studio (SSMS).
- A client application such as Power BI Desktop or Excel.
This tutorial is based on Adventure Works Cycles, a fictitious company. Adventure Works is a large, multinational manufacturing company that produces and distributes bicycles, parts, and accessories for commercial markets in North America, Europe, and Asia. The company employs 500 workers. Additionally, Adventure Works employs several regional sales teams throughout its market base. Your project is to create a tabular model for sales and marketing users to analyze Internet sales data in the AdventureWorksDW database.
To complete the tutorial, you must complete various lessons. In each lesson, there are tasks. Completing each task in order is necessary for completing the lesson. While in a particular lesson there may be several tasks that accomplish a similar outcome, but how you complete each task is slightly different. This method shows there is often more than one way to complete a task, and to challenge you by using skills you've learned in previous lessons and tasks.
The purpose of the lessons is to guide you through authoring a basic tabular model by using many of the features included in SSDT. Because each lesson builds upon the previous lesson, you should complete the lessons in order.
This tutorial does not provide lessons about managing a server in Azure portal, managing a server or database by using SSMS, or using a client application to browse model data.
This tutorial includes the following lessons:
|Lesson||Estimated time to complete|
|1 - Create a new tabular model project||10 minutes|
|2 - Get data||10 minutes|
|3 - Mark as Date Table||3 minutes|
|4 - Create relationships||10 minutes|
|5 - Create calculated columns||15 minutes|
|6 - Create measures||30 minutes|
|7 - Create Key Performance Indicators (KPI)||15 minutes|
|8 - Create perspectives||5 minutes|
|9 - Create hierarchies||20 minutes|
|10 - Create partitions||15 minutes|
|11 - Create roles||15 minutes|
|12 - Analyze in Excel||5 minutes|
|13 - Deploy||5 minutes|
These lessons are not required to complete the tutorial, but can be helpful in better understanding advanced tabular model authoring features.