The terms “DirectQuery” and “Connect Live” are somehow confusing. I saw lots of people are using both terminologies as alternatives. But, the context of “DirectQuery” and “Connect Live” are very different indeed. Therefore, if use a a terminology when we’re talking about a different context then the whole situation might get quite confusing. in this post I try to explain the differences and make it more clear to prevent using a wrong terminology and make sure everyone is on the same page when we’re referring to “DirectQuery” or “Connect Live”.
When we use the “DirectQuery” terminology we are actually talking about connecting from Power BI Desktop instance to an RDBMS type of data source like SQL Server DB or Oracle DB.
There are two types of data connections when we’re connecting to RDBMS like SQL Server or Oracle DB from Power BI Desktop:
Import Data: which literally loads data into the underlying model to make it available in memory
DirectQuery: which doesn’t load data into model. Instead, it runs multiple concurrent queries on the RDBMS side (data source side) and gets the results. This is good to support real-time data processing.
Note: The same principal applies to SSAS Tabular.
On the other hand, when talk about “Connect Live”, we are referring to the data connection type from a reporting tool like Power BI Desktop OR Excel to an instance of SSAS, either SSAS Multidimensional or SSAS Tabular.
From April 2017 onward we can use On-premises Data Gateway for Azure Analysis Services. This means you can connect your Tabular Models hosted in Azure Analysis Services to your on-premises data sources through On-premises Data Gateway. In this post you learn how to setup and configure the On-premises Data Gateway as well as how to configure Azure Analysis Services to connect to the on-premises database(s) via the gateway.
Requirements/Assumptions
You have an Azure subscription
You already have an up and running instance of Azure Analysis Services (AAS)
Your instance of Azure Analysis Services, your instance of Power BI Service and your On-premises Data Gateway are all in the same “Region” (Check Prerequisites section below for more details)
This post covers the most common scenario which doesn’t involve Kerberos, Proxy Server, OKTA etc…
Reading: If you are not that familiar with On-premises Data Gateway then I encourage you to read this and for more in-depth read this article. You may also watch this video from Adam Saxton discussing On-premises Data Gateway.
Prerequisites
As stated in the “Requirements” section, it is important to check if your instances of Azure Analysis Services, Power BI Service and On-premises Data Gateway located in the same “Region”.
The reasons behind that are:
Your On-premises Data Gateway MUST be installed in the same Region as your Power BI Service sits in. Otherwise your Power BI cannot see the gateway, therefore, you’re unable to schedule automatic data refresh in Power BI Service
To get the best performance and more reliability, you have to create On-premises Data Gateway Resource in Azure side in the same region as your Azure Analysis Services lives in
But, in some cases people created their Power BI account a long time ago and perhaps they didn’t set the right region for their Power BI Service to sit in. Now, they need to create an instance of Azure Analysis Services, but, due to their organisation privacy and security, they don’t want to (or perhaps not allowed to) create the instance of Azure Analysis Services in the region that their Power BI tenant sits in. So they would prefer to create the Azure Analysis Services in another region. In that case, it is recommended to install a new instance of On-premises Data Gateway in a separate server and change the “Gateway Region” during the installation.
To check the “Region” of your instances follow the steps below:
Power BI Service Region:
Login to your Power BI Service
Click the question mark on top right side of the page
I recently spoke in Tampa Dev Azure Meeting in a webinar form on 31st Jan 2018. We received interesting questions during the presentation. My aim was to introduce basic concepts of Big Data, Azure Data Lake, Azure Data Lake Store (ADLS), Azure Data Factory (ADF) and Power BI.
I would like to thank Tampa Dev organisers and all attendees for giving the opportunity to speak in this session.
Technology is growing fast and we are enjoying it. We reshape our daily created data in a form that satisfies our needs. One of the technologies which is used more commonly these days is SQL Server Tabular Models, SSAS Tabular in short. Lots of industries decide to go with SSAS Tabular in their new projects and some defined new projects to slowly switch their existing SSAS Multidimensional to SSAS Tabular. I know, there is a big debate around SSAS Multidimensional vs. SSAS Tabular. But my aim is to prevent going through that sort of discussion. As the title implies, this post is about documentation that I believe is one of the most important parts of every project which is also sacrificed the most. In this post I explain how to document your SSAS Tabular model in Power BI Desktop and Excel. I know, there are some products you can find in the internet that can generate documentation in various formats like Word, PDF, HTML and so on. But, If you’re looking for a free and somehow more intuitive way of documenting your SSAS Tabular Models with Power BI then this article is for you. Through this article, we create a documentation tool with Power BI. I call it SSAS Tabular Model Documenter. In this method we don’t use DMVs at all. For those who are not familiar with DMVs I shortly explain what DMVs are, if you’re already familiar with DMVs you can jump this section.
You can download a copy of SSAS Tabular Model Documenter in Power BI template format (pbit) at the end of this post. It is a Christmas present for you.
What are DMVs?
Dynamic Management Views, DMVs in short, are queries that retrieve metadata information about an instance of SQL Server Analysis Services. DMVs work on both SSAS Multidimensional and SSAS Tabular server modes. DMVs can be used to monitor server operations and health. The DMV query structure is very similar to T-SQL, therefore you use “SELECT” statement followed by “$System” which is an XMLA schema rowset. The DMV queries look like below:
SELECT * FROM $System.<schemaRowset>
So you can open SQL Server Management Studio, connect to an instance of SSAS (Tabular model for the sake of this post) and run the following query to get lots of information about tables in your Tabular model:
Note:This method only works with SSAS Tabular 2016 and above.
Document SSAS Tabular without DMVs
In SSAS Tabular 2016 and above there is a tiny metadata database that can be loaded in Power BI Desktop or Excel to document the corresponding SSAS Tabular model. The database is a SQLite database. In the previous post I explained how to visualise SQLite data in Power BI. The requirements for this post are the same as the previous post, so I encourage you to check it out. Therefore, I just explain how to find the metadata file and how to build a model in Power BI Desktop. I also explain how to do the same in Excel for those of you who would like to add some annotations or comments to the outcomes.
