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Hands-On SQL Server 2019 Analysis Services

Hands-On SQL Server 2019 Analysis Services

By : Steven Hughes
5 (6)
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Hands-On SQL Server 2019 Analysis Services

Hands-On SQL Server 2019 Analysis Services

5 (6)
By: Steven Hughes

Overview of this book

SQL Server Analysis Services (SSAS) continues to be a leading enterprise-scale toolset, enabling customers to deliver data and analytics across large datasets with great performance. This book will help you understand MS SQL Server 2019’s new features and improvements, especially when it comes to SSAS. First, you’ll cover a quick overview of SQL Server 2019, learn how to choose the right analytical model to use, and understand their key differences. You’ll then explore how to create a multi-dimensional model with SSAS and expand on that model with MDX. Next, you’ll create and deploy a tabular model using Microsoft Visual Studio and Management Studio. You'll learn when and how to use both tabular and multi-dimensional model types, how to deploy and configure your servers to support them, and design principles that are relevant to each model. The book comes packed with tips and tricks to build measures, optimize your design, and interact with models using Excel and Power BI. All this will help you visualize data to gain useful insights and make better decisions. Finally, you’ll discover practices and tools for securing and maintaining your models once they are deployed. By the end of this MS SQL Server book, you’ll be able to choose the right model and build and deploy it to support the analytical needs of your business.
Table of Contents (19 chapters)
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1
Section 1: Choosing Your Model
4
Section 2: Building and Deploying a Multidimensional Model
8
Section 3: Building and Deploying Tabular Models
12
Section 4: Exposing Insights while Visualizing Data from Your Models
15
Section 5: Security, Administration, and Managing Your Models

What's new in SQL Server Analysis Services 2019?

The focus of this book is on using SSAS 2019. What has Microsoft added to the product in its most recent release? Because Analysis Services is effectively broken into two types of databases – multidimensional and tabular – we will talk about the changes to each separately.

Multidimensional models in 2019

This is the short list. Microsoft has not made significant changes to multidimensional capabilities in Analysis Services since the SQL Server 2012 release. Even that release focused on the new xVelocity In-Memory Analytics Engine (aka Vertipaq) that would support tabular models. Microsoft considers the multidimensional model in Analysis Services mature and is not adding major features at this point. The focus is on bug fixes and various performance enhancements to the engine. The key takeaway here is that multidimensional models still have a place but are not receiving any significant updates. The following is from Microsoft's documentation:

Multidimensional mode and Power Pivot for SharePoint mode are staples for many Analysis Services deployments. In the Analysis Services product lifecycle, these modes are mature. There are no new features for either of these modes in this release. However, bug fixes and performance improvements are included.

Source

https://docs.microsoft.com/en-us/analysis-services/what-s-new-in-sql-server-analysis-services#sql-server-2017-analysis-services

Tabular models in 2019

While multidimensional models are considered mature, Microsoft is continuing to make significant investments in tabular model technology. Since its release in 2012 until now, major changes have happened with tabular models.

Compatibility levels

When working with tabular models, you need to understand compatibility levels. Microsoft introduced compatibility levels to allow new versions of Analysis Services to be backward compatible while enabling significant changes to supported features. When creating a tabular model, it is recommended to use the most current compatibility level. However, if you have an existing model and want to upgrade to the latest SQL Server version, you can set your compatibility level to what you are currently running until you have a chance to update the level and test it with the new features. The compatibility level is set when creating a new project in Visual Studio.

SQL Server 2019 supports the 1500 (SQL Server 2019), 1400 (SQL Server 2017), and 1200 (SQL Server 2016) compatibility levels. The features released with SQL Server 2019 are included in compatibility level 1500.

Here are some of the key updates included with SQL Server 2019 Analysis Services (compatibility level 1500):

  • Query interleaving
  • Calculation groups in tabular models
  • Governance setting for Power BI cache refreshes
  • Online attach
  • Many-to-many relationship support

Let's look at each of these changes in terms of what they are and why they matter.

Query interleaving

Query interleaving allows you to set how queries are handled based on query length and performance. Tabular model queries are handled in a first-in, first-out model (FIFO) by default. This means that a long-running query could make shorter queries run for longer if they follow that query in the queue. By enabling this feature, shorter queries can be executed during a long query run. This feature is only available for import models, not Direct Query. However, if you have a high-concurrency tabular model solution (lots of users or complex queries), this feature could improve performance for your users and reduce CPU pressure on the server.

Calculation groups

Calculation groups are used to group related calculations, which users often work with at the same time. This is really helpful with large complex models with many different calculations for the users to navigate. Microsoft calls out that Time intelligence will benefit from this significantly. For example, you can create a calculation group that has Current, Month-to-Date (MTD), Quarter-to-Date (QTD), and Year-to-Date (YTD) and call it xTD. When the user views the deployed model, they will see a calculation group as a single column they can add to their visual, which displays all four of these calculations as applied to a base measure such as Revenue. This feature has been added to improve usability in complex models.

Governance settings for Power BI cache refresh

The Power BI service caches data for dashboards and reports to improve performance and user experience when using live connections with tabular models. However, in some cases, this can cause a significant amount of queries with the possibility of overloading a server. This setting will override background refresh policies set on the client, preventing performance issues on the server.

Online attach

Currently, updates to tabular models require the model to be taken offline while deploying changes to the model. This results in downtime for the model. This feature allows model designers to deploy model changes live. This is similar to the shadow copy feature with multidimensional models, which supports the same online deployment.

The process currently is supported using XML for Analysis (XMLA) (more about that later). However, for tabular models, you will need to account for double the model's memory footprint during the online attach operation. The effective result is that during the attach process, both the new model and the old model will be in memory during the process. Once the process has completed, the old model will be removed. During the operation, users can continue to query the model and will start using the new model once it is loaded.

Many-to-many relationship support

Many-to-many relationship support has always been an issue with tabular models. This change allows relationships to be created between two tables where the relationship may not be unique. For example, if you have a fact table that is aggregated to the month, you will now be able to use the month value from a date table that has daily granularity. This allows cleaner, simpler models that are easier to use. Next, we will look at the tools that are used with SSAS.

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