At bare minimum we’ll most likely be using Visual Studio, Team Foundation Server for version control, possibly SSIS, SQL Databases and SSAS. Suffice to say, you’re looking at a much heftier investment regardless.Īnother drawback to this connection is that we are now pulled out of the Desktop as a standalone solution and thrown into development areas. This post won’t go into details because there is a myriad of options out there and the number of options increase exponentially when you start comparing Azure to on-premises. When you scale up and start to use enterprise level tools you need to look at the costs that those include.
(Desktop is free, but let’s just call it $10 because you need a Pro license to share). It is amazing the amount of power and value you get for $10/month. Without a doubt one of the most appealing aspects of Power BI is the price. This means that if you have a couple measures you need to add to a single report, you can easily add those in the Power BI Desktop without the need to have them added to the model. However, a really great addition in the May 2017 Desktop release was the addition of allowing measures to be created on top of the live connection. The expectation is that you are doing all the data mashup / ETL and modeling behind the scenes and as such, these features are all removed. Power BI has become only the front end of the process. Data pane, DAX tables, Calculated columns? Gone. As with Direct Query, there are features and capabilities in the Power BI Desktop that are just flat out turned off or completely gone. This is without a doubt the most intimidating to the end user that isn’t familiar with the live connection. Notice: the Data and Relationships icons are not visible after making a Live Connection. Most limiting of all in terms of disabling Power BI features.That being said, lets dive into the details of what a centralized model gives us, and the pros & cons of the Power BI Live Connection. SQL Server Analysis Services Tabular is the typical implementation that I see most often employed due to the relational nature, compression, in memory storage and speed. This centralized approach is imperative in order for large scale BI initiatives to be successful. The evolution of a Power BI solution “should” typically land in a space where a centralized or several centralized models are being used as the backbone for the vast majority of Power BI reports. You can deploy a single dataset to the Service and re-use it to build multiple reports! Having your own instance of Analysis Services on premises or Azure lets you maximize your development and deployment efforts and truly create a sustainable reporting solution.
In fact, each time you build a Power BI report in the Desktop, you are building a Tabular model that is then created in the cloud upon publish! This live connection method allows you to gain a bit more control. Anyone who uses the “Power BI Service” connector that was first made available in April 2017 and released to GA in August 2017 is using a live connection to an Analysis Services Instance hosted in in your Power BI tenant. Before we dive into the deep stuff, are you aware that you can use this connection type without your own instance of Analysis Services? Let me explain.