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.
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.
As the name implies, SQLite is a light weight transactional SQL database engine. It is open-source and free for use either for personal commercial. SQLite is widely used in mobile apps and many other desktop applications that need an internal light weight free SQL database. In this post I explain how to visualise SQLite data in Power BI.
Requirements
To be able to go through the process you need to meet the following requirements:
Latest Version of Power BI Desktop (Current version: 2.52.4921.682 64-bit (November/2017))
Install SQLite ODBC driver: Make sure you install 64 bit version if your Power BI Desktop is 64 bit version like mine!
Note: You may install both x32 and x64 bit versions of the driver if your other applications are in x32 bit.
Like any other Power BI cases, it’s really easy to load data from an existing SQLite database to a Power BI Desktop model. You just need to use ODBC data connection and connect to a predefined “ODBC DNS” OR use a “Connection String”. I’ll explain both methods. After you load data to your Power BI Desktop, you create the relationships then you’re good to go and create flashy reports. Continue reading if you’re interested to an step-by-step guide to visualise SQLite data In Power BI.
Importing SQLite Data to Power BI Using ODBC DSN
Open the correct version (x32, x64) of ODBC after you downloaded and installed SQLite ODBC Driver
Click “Drivers” tab and make sure SQLite ODBC Driver(s) successfully installed
