Unlocking the Power of Tabular Modeling In Microsoft SQL Server Analysis Services

Are you ready to take your data analysis to the next level? Look no further than Microsoft SQL Server Analysis Services! In this article, we'll explore the wonders of tabular modeling in SQL Server Analysis Services and how it can revolutionize your data analysis projects.

What is Tabular Modeling?

Tabular modeling is a popular approach to designing analytical data models in SQL Server Analysis Services. It provides a powerful way of visualizing and analyzing large datasets by using tables and columns, similar to a traditional spreadsheet. The key difference is that tabular models are hosted in SQL Server Analysis Services, enabling advanced data analysis capabilities.

Tabular Modeling in Microsoft SQL Server Analysis Services (Developer Reference)

by Marco Russo(2nd Edition, Kindle Edition)

4.7 out of 5

Language	:	English
File size	:	91224 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	488 pages
Screen Reader	:	Supported

FREE

Benefits of Tabular Modeling

Tabular modeling offers numerous advantages for developers and analysts:

• In-Memory Processing: Tabular models reside entirely in memory, allowing for rapid query performance and real-time analytics.
• Natural Language Query: SQL Server Analysis Services supports natural language query processing, enabling users to ask questions using everyday language.
• Columnar Storage: With a columnar storage format, tabular models efficiently compress data and enhance query performance.
• Data Integration: Tabular models can integrate with various data sources, including databases, Excel files, and even cloud-based services.
• Role-Based Security: SQL Server Analysis Services provides robust security features, allowing you to control access to sensitive data based on user roles.

Getting Started with Tabular Modeling

If you're new to tabular modeling, here are the essential steps to get started:

1. Install SQL Server Analysis Services: Make sure you have SQL Server Analysis Services installed on your machine.
2. Create a Tabular Model Project: Launch SQL Server Data Tools and create a new tabular model project.
3. Define Data Sources: Connect your tabular model to the appropriate data sources, such as SQL Server databases or Excel files.
4. Create Tables and Relationships: Design your tabular model by creating tables and establishing relationships between them.
5. Define Measures and Calculated Columns: Enhance your tabular model by defining measures and calculated columns to perform calculations and aggregations.
6. Deploy and Process the Model: Deploy your tabular model to SQL Server Analysis Services and process it to load data.
7. Explore and Analyze: Use various tools, such as SQL Server Management Studio or Power BI, to explore and analyze data from your tabular model.

Best Practices for Tabular Modeling

To ensure efficiency and maintainability, here are some best practices to follow when working with tabular models:

• Keep It Simple: Avoid unnecessary complexity in your tabular models. Focus on the most critical business requirements.
• Normalize Data: Normalize your data model by breaking it down into smaller tables with clear relationships.
• Use Hierarchies: Utilize hierarchies to enhance user experience and facilitate drill-down analysis.
• Secure Your Model: Implement role-based security to control access to sensitive data.
• Regular Updates: Ensure regular updates to your tabular model to reflect changes in underlying data sources.

Tabular modeling in Microsoft SQL Server Analysis Services offers a robust and flexible solution for analyzing large datasets. By utilizing tabular models, developers and analysts can unlock advanced data analysis capabilities, improve performance, and gain valuable insights. Follow the best practices mentioned in this article, and you'll be well on your way to becoming a proficient tabular modeler. So, what are you waiting for? Dive into the world of tabular modeling and revolutionize your data analysis projects today!

Tabular Modeling in Microsoft SQL Server Analysis Services (Developer Reference)

by Marco Russo(2nd Edition, Kindle Edition)

4.7 out of 5

Language	:	English
File size	:	91224 KB
Text-to-Speech	:	Enabled
Enhanced typesetting	:	Enabled
Print length	:	488 pages
Screen Reader	:	Supported

FREE

Build agile and responsive business intelligence solutions

Create a semantic model and analyze data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model.

Discover how to:

• Determine when a tabular or multidimensional model is right for your project

• Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015

• Integrate data from multiple sources into a single, coherent view of company information

• Choose a data-modeling technique that meets your organization’s performance and usability requirements

• Implement security by establishing administrative and data user roles

• Define and implement partitioning strategies to reduce processing time

• Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks

• Optimize your data model to reduce the memory footprint for VertiPaq

• Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models

• Select the proper hardware and virtualization configurations

• Deploy and manipulate tabular models from C# and PowerShell using AMO and TOM libraries

Get code samples, including complete apps, at: https://aka.ms/tabular/downloads

About This Book

• For BI professionals who are new to SQL Server 2016 Analysis Services or already familiar with previous versions of the product, and who want the best reference for creating and maintaining tabular models.

• Assumes basic familiarity with database design and business analytics concepts.