Power BI is a great tool for creating data mashups and great visualizations. There are a lot of posts on how and why to use Power BI for these tasks, including mine. After working with a number of clients on how to make implement Power BI in their data environments, I thought it might be helpful to talk about how Power BI works internally to provide guidance to determine how best to implement it. One of Power BI’s big strengths is the ability to bring data in from a lot of different sources and put them together into a single data model. Power Pivot in Excel and Power BI Desktop in the Relationship’s page both allow you to create data models. Power BI on the web, does not, as of this writing allow the ability to create data models from multiple sources. Power BI is able to handle a large amount of data to be stored within it using the Vertipaq engine which compresses the data and loads it in memory. How much data? Well that has to do with how much memory you have.
Having 8 GB of Memory on a 32 bit Operating System is Worthless
Recently I was working at a client who wanted to load five year’s worth of operating information into Power BI. He knew that Power BI needs a lot of RAM, so he requisitioned 8 GB of RAM for his laptop so he would be able to load this much data. However, his IT department had a policy of only installing 32 bit operating systems on the computers. When 64 bit operating systems first became available, often times the computer bios or the mother board wouldn’t support it. Until very recently, outside of developers, most people didn’t have a business reason for 64 bit operating system to do their job.
Power BI will use all the memory you have available. What is available? Here’s some math to explain how much memory is available. A 32 bit Windows operating system can assess 2 32 = 4GB of RAM, and you don’t even get all of that as the system uses some of it. This math applies if a 32 bit version of Office 2013 is installed onto a 64 bit version of the operating system. The client couldn’t load five years of operational data into Excel because he didn’t have enough addressable memory, since with a 32 bit operating system he had 4 GB of RAM he can use, period.
Reasons for Data Modeling in Excel Power Pivot
Power BI is a great tool, but it is not the only tool. If you want to load up years of data into your model, at some point, even if you have a 64 bit OS and 32 GB of RAM, eventually you will run out of memory. Well then what do you do? If you have developed your data model in Excel, no problem you can upgrade it to Analysis Services Tabular. Visual studio has a tool to make migrating to Analysis Services Tabular easy to do. I find Power Pivot model to be one of the best ways to get started on creating a Tabular Model as you can test out your data modeling concepts very quickly. If you have developed your data model in Power BI Desktop, as of this writing there is no way to migrate directly to Analysis Services Tabular. If you are familiar with Power BI, you may be pleasantly surprised at how similar Analysis Service Tabular is. Along with improved performance accessing the data, there are a number of security features which are not available in Power BI in Analysis Services Tabular. With Power BI, you can create a corporate solution from a desktop application, which is one of the neatest things about Power BI.
Data aficionado et SQL Raconteur