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Category: SSAS

OLAP Acronym returns

OLAP Acronym returns

After reviewing Azure Data Architecture Guide, I noticed the label Online Analytical Database (OLAP) referenced as the description for Azure Analysis Services. I will call Azure Analysis Services AAS from here on. The AAS is using tabular models and not multidimensional cubes. Lately, OLAP has not been seen as an overall description of the tabular model. There were references to semantic model replacing cube’s data source view. It is good to see this in official Microsoft documentation. While recording or…

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Analysis Services Series on SQLShack

Analysis Services Series on SQLShack

Please visit SQLShack.com for new articles on many facets of SQL Server. I have been trying my best to document how to create SQL Server Analysis Service databases with Multidimensional Cubes as well as Tabular Models. The start was a Best Practices article for Dimensional Modeling and other items that help with a smooth transition to creating an SSAS database. Here is a link to that article. The flow of the articles starts with the multidimensional cube, then the next…

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Live! 360–Speaking at SQL Server Live Orlando 2016

Live! 360–Speaking at SQL Server Live Orlando 2016

If you are looking for a great conference to attend, please look at Live! 360. This event combines 6 different areas of IT (including SQL Server) with some of the great experts presenting sessions for 5 days. The sessions are on December 5th thru the 9th in Orlando, FL at Royal Pacific Resort. This is a link with a discount code for up to $500 dollars off – http://bit.ly/LSPK47_REG Here are the three I am giving. SQT07 New Performance Tuning…

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Why use a Date Dimension Table in a Data Warehouse

Why use a Date Dimension Table in a Data Warehouse

In the Data Mart, or the Data Warehouse world, there is a date dimension table in all schemas if you are using the Kimball Dimensional Modeling method. In the beginning of Dimensional Modeling, it was called a Time dimension. Since then, the Time dimension has actually been separate from the date values. After listing all these terms: time, date, dimensional modeling, data mart, data warehouse, etc., you might be more confused than ever about what we are talking about. So,…

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Analysis Services: Solving Hierarchy Errors of Uniqueness

Analysis Services: Solving Hierarchy Errors of Uniqueness

Multidimensional Cubes provide speed when it comes to retrieving aggregations that are important to business decisions. Being able to slice or group the measures by dimension attributes helps with a quick analysis and flexible/interactive reporting. Configuring these attributes as hierarchies has some details that are not at first obvious. The error message when these problems exist is not extremely helpful for someone new to cubes. Let’s look at creating a Date hierarchy with Year, Quarter, Month and Day. Our cube…

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