In one more quick post, I would like to share with you some materials to learn about SQL / Azure Analysis Services (SAAS / AAS) without paying anything – FOR FREE! If your excuse for learning about this semantic and processing layer, which allows you to use BILLION rows of datasets in a few seconds in Power BI, now it's over!
For those unfamiliar, Azure Analysis Services (AAS) / SQL Server Analysis Services (SSAS) is a Microsoft solution, whose goal is to promote a semantic layer to abstract measures, calculated columns, relationships, management, alerts, monitoring, governance, security, object documentation and all the technical part of a data model so that IT cares about that, leaving the dataset intact, validated and performant so that end users can connect to these cubes and consume the data in the format Self-Service, without relying on IT to create reports, and all of this in an organized, controlled way, allowing you to work with gigantic volumes of data (BILLIONS of lines) and with exceptional performance.
We basically have three versions of the product:
- SQL Server Analysis Services – Multidimensional: On-premises installation that is part of the SQL Server licensing, available since the 2005 version and aims to solve some very complex problems for tabular cubes, besides performing very well with data volumes that surpass the amount of RAM memory available. It uses MDX language for query, much more complex than the DAX language of the tabular model. Does not allow you to create new measures in Power BI when connected to this type of data source
- SQL Server Analysis Services – Tabular: On-premises installation that is part of the SQL Server licensing, available since the 2012 version and aims to simplify the creation of cubes. He was responsible for the VertiPaq engine, the basis of Power BI, which applies columnar compression, which can reduce the size of the model by up to 10x. It prioritizes memory usage, so it's usually faster than the Multidimensional Cube, but it doesn't support such large data volumes. It uses DAX language for query (the same as Power BI) and we can create new measurements using Power BI Desktop
- Azure Analysis Services (Only tabular): 100% Cloud installation as PaaS. It has the same features as SQL Server Analysis Services – Tabular, but is updated more frequently and therefore has more features and improvements
So, here are some materials to learn more about these products without spending anything and without leaving home.
Articles on Analysis Services
- Analysis Services - Creating Your First Multidimensional Cube in the Star Model (Star Schema)
- Analysis Services - Querying catalog views from SQL Server
- Analysis Services (SSAS) - How to query information and process command line (XLMA) commands through SQL Server
- Analysis Services - How to use XLMA to backup and restore cubes via the T-SQL command line
- Analysis Services - How to use XLMA or Powershell to process cubes and dimensions via command line (T-SQL) or SQL Agent Job
Power BI and Analysis Services – Lecture 1 – Performance, Security and Governance Overview
In this long-awaited and requested video by our followers, today we are starting a series of videos about Power BI and Analysis Services – How to deliver Performance, Security and Data Governance, where we will demonstrate how to consume 1,5 BILLION records instantly in Power BI, plus much more!
Power BI and Analysis Services - Lesson 2 - Local (On-premises) vs Cloud (Cloud)
In the second video of the long-awaited and requested by our followers, training on "Power BI and Analysis Services - How to deliver Performance, Security and Data Governance", I will demonstrate the differences, advantages and disadvantages between the use of Analysis Services On-Premises ( on-premises) or in the cloud (Cloud / Azure) to help you decide which contraction form best suits your BI projects.
Power BI and Analysis Services - Lecture 3 - Tabular vs Multidimensional
In the third video of the long-awaited and requested by our followers, “Power BI and Analysis Services – How to Deliver Performance, Security and Data Governance” training, I will demonstrate the differences, advantages and disadvantages between the Tabular and Multidimensional data models of Analysis Services to help you decide which model to use in each scenario of your BI projects.
Tabular or Multidimensional? Which model should I use?
In this session you will learn about the main differences between SQL Server Analysis Services Multidimensional and Tabular models. We will also see, according to the main positive and negative points, where to fit each of them into an Enterprise project. We'll also look at where and when to use the SSAS Tabular PaaS model in Azure.
Power BI and Analysis Services - Lecture 4 - Installation, Configuration, Contracting in Azure and Connection
In this 4th video class of the “Power BI and Analysis Services” series, I will demonstrate how to prepare the environment before starting the OLAP cube project
Power BI and Analysis Services - Lesson 5 - How to create a Tabular cube
In this 5th video class of the “Power BI and Analysis Services” series, I will demonstrate how to create your first Tabular cube, showing the creation of measurement tables, documentation, creation of hierarchies, publishing the finished cube and querying the cube created in the video.
Happy Hour with Data # 9 - From Application to Dashboard
In the ninth live of "Happy Hour with Data", we present an end-to-end BI project: ETL creation with Azure Data Factory and Azure Logic Apps, data being written to SQL Server and MongoDB, an API using NodeJS will be created to make available this data, Creating a model in Azure Analysis Services and reading this data using Power BI. This data will still be brought back to SQL Server using SSIS!!
We demonstrate in this live how this project works all integrated and thus, we demonstrate an end-to-end BI project, like you've never seen live.
Nerdzao #213 – Power BI and Analysis Services
Power BI and Analysis Services – 1,5 billion rows in 1 second: In this presentation, I demonstrated the full potential of using Power BI by consuming tens of millions of rows from Azure Analysis Services, delivering performance, governance, and security to your analytics of data
That's it folks!
A big hug and until next time!