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There are however some limitations with Live connection which I’ll explore later in this post. DirectQuery means Live Connection.Īfter creating the live Connection you can create relationship in the model, or build visualization for that. When you go through Get Data and select this table (or any other tables in the data set) and click Load, you’ll see the option to choose between Live connection or Import. this table is big enough to show how live connection works for this example. I know it is not more than 10GB, but the method would be the same even if I have 10TB sized data table. I have a database with a large table contains 48 million records of data. Let’s look at an example of such Live connection to SQL Server on premises database. Live Connection to SQL Server On Premises with every visualization a query will be sent to the data source and brings the response. Live connection brings the metadata and data structure into Power BI, and then you can visualize data based on that. Live connection won’t import data into the model in Power BI. You can have a SQL Server, Oracle or whatever data source you want with any size of data you need, and create a live connection to it with Power BI. Well, here’s the trick if your data set is large, then use Live connection! simple but useful trick.
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With Power BI we can connect live to some data sources On premises or in cloud. The bottom line in this section is that, if you have a data set that is more than 10GB and won’t grow significantly, then consider loading that into Power BI to check how compressed it would be, maybe you get it under 10GB limitation and then you are good to go ? If that is not the case then continue reading. However compression rate isn’t always like that, it depends on type of data set, data type of columns and some other facts. When it loaded into Power BI I had only 8MB power BI file to work with. Any data set will be compressed in a reasonable level when you import the data into Power BI.Īs an example I’ve imported a CSV file with ~800 MB data size. Compression happens automatically, that means you don’t need to set a configuration, or allow Power BI to do something. Compressed Structure of Power BIįirst of all I have to mention that Power BI compress each data set effectively before loading into memory, this is one of the big advantages of xVelocity In-memory engine that Power BI, Power Pivot, and SSAS Tabular built on top of that. As any other solutions there are pros and cons of working with large data sets with Power BI, Let’s explore them together. Is Power BI limiting you for the visualization? Short answer No! In this post I’ll explain you options that you have when you deal with large data sets. However in many organizations you have much bigger size of data than 10GB, sometimes you deal with Tera bytes, even Peta bytes of data.
#Limitation of quiri pro#
Power BI free allows you to have 1GB data per user, and pro 10GB.