![]() Power BI leverages the compression engine of xVelocity and works on a Column-store in-memory technology. The very first assumption that you might get after reading the above explanation about Import Data is that if you have a database with 100 GB, then if you import it into Power BI, you will get a 100 GB file size in Power BI. Bottom line is that you spent memory and disc space as much as you load data into Power BI. If you have a database with 1000 tables, however, you only load 10 of those tables in Power BI, then you get memory consumption for only those 10 tables. If you have 1 Million rows in a source table, and you load it into Power BI with no filtering, you end up having the same amount of data rows in Power BI. When you publish the report on the website, then it will be the memory and disk space of the Power BI cloud machines. As long as you are developing Power BI on your machine with Power BI Desktop, then it would be the memory and disk space of your machine. Loading in Power BI means consuming memory and disk space. With this method data from the source will be loaded into Power BI. Both names explain the behavior of this method. This method has two names, some call it Import Data, and some call it Scheduled Refresh. ![]() What is Import Data or Scheduled Refresh? What are Architecture Scenarios to use for Each Method?.Which method is performing best and fastest?.What is the Difference between Live Connection and DirectQuery?.In this post, I’m going to explain in detail what every method is, and the answer to all questions below So the best would be to choose the right method from the beginning.Ĭhoosing the right method is an important step for your Power BI Solution Architecture, which you need to decide about it usually in the early phases before starting implementation. Changing from one method to another method can be a time-consuming task after a while in the implementation process. Depending on the scenario that you are implementing Power BI for, you might choose one way over the others. Each method has some benefits and also some disadvantages. You will learn later in this post about their differences. Many of you might still think that DirectQuery and Live Connection are the same, however, they are different. However, Power BI supports multiple different methods for connecting to data: DirectQuery, Live Connection, Import Data (or some call it Scheduled Refresh), and Composite Model. You never needed to choose between methods and find the right method for yourself. If Power BI only had one way to connect to data sources, then everything was easy. If you like to learn more about Power BI read the Power BI book from Rookie to Rock Star. This post helps you to choose the right data connection methodology and architecture for your Power BI solution. ![]() In this post, you are going to get the answer to all questions above. I always get a lot of questions like this in my courses, conference talks, and blog posts. What do these actually mean? and what is the situation in which you should choose one over the other one? What are the pros and cons of each? What are the best practices to choose each? Which one is faster? which one is more flexible? Is DirectQuery and Live Connection actually one thing? or two separate methods? And many other questions. You have heard of DirectQuery, Live Connection, Import Data, and there is also a Composite Model. That is why the decision to choose the right method is always a tough decision. Power BI supports different methods for connecting data.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |