On-premises Data Gateway (aka Power BI Enterprise Gateway) is release a while ago (2 Dec. 2015), but, with the latest release on 22 Dec. 2015 Power BI Enterprise Gateway now supports live connections to both SQL Server Analysis Services Multidimensional and Tabular models as well as SAP HANA. In this post I’ll explain lots of important aspects of the Power BI Enterprise Gateway including installation, configuration for different data sources including SSAS Multidimensional, Tabular and SQL Server Database and much more. If you need to have the lowest possible latency then you need DirectQuery/Explore Live feature on top of your on-premises data sources. The good news is that Power BI Enterprise Gateway now supports all following data sources:

SQL Server Database
SQL Server Analysis Services Multidimensional
SQL Server Analysis Services Tabular
SAP HANA
In this article you’ll learn how to install and configure Power BI Enterprise Gate Way, how to manage different live data sources, how to create reports on top of live data sources and more.
Note 1: If you want to use DirectQuery to connect to your on-prem SQL Server Database OR Explore Live your SQL Server Analysis Services Tabular model then you might not need to install and use the Power BI Enterprise Gateway. In those cases you can install Power BI Personal Gateway to connect to an instance of SQL Server OR install Power BI Analysis Services Connector to connect to your on-prem instance of SQL Server Analysis Services Tabular model rather than installing the Power BI Enterprise Gateway. But, bear in mind that selecting the best gateway is really depending on your use cases, your data sources and the environment you’re working on.
Note 2: The Power BI Enterprise Gateway and Power BI Personal Gateway CAN be installed on the same machine.

Downloading and Installing Power BI Enterprise Gateway

You can download the gateway from the dedicated download page for On-premises Data Gateway on Microsoft website or after logging into Power BI Service with your account, click on “Data Gateway” from the download menu:

OR you can go straight to the gateway page then download the Power BI Gateway – Enterprise (Preview):

Continue reading “Power BI Enterprise Gateway, Everything You Need to Know” →

Without a doubt cloud computing is going to change the future of data analytics and data visualisation very significantly. Microsoft Azure SQL Data Warehouse recently released for public preview. Combining Power BI as a powerful data visualisation tool with Azure SQL Data Warehouse will give the users the ability to see data insights of their data stored in Azure Data Warehouse very easily. In this post I explain how to install Azure SQL Data Warehouse and the the way it works with Power BI. Before going any further I’d like to have a look at the Azure SQL Data Warehouse very briefly.

What Is Azure SQL Data Warehouse?

Based on Microsoft documentation a SQL Data Warehouse is

“Azure SQL Data Warehouse is an enterprise-class distributed database capable of processing petabyte volumes of relational and non-relational data.”

Azure SQL Data Warehouse supports stored procedures, user-defined functions, indexes and collations. It uses columnstore index technology which significantly improves query performance as well as getting you up to 5 times compression in compare with traditional row based indexing.

I leave it to you learn more about Azure SQL Data Warehouse. But, it is important to keep in mind that there are some features like primary keys and foreign keys that are NOT supported in Azure SQL Data Warehouse which affect the way we use Power BI as a data visualisation tool over Azure SQL Data Warehouse. Without primary keys and foreign keys there is no physical relationships between the tables so Power BI service cannot detect any relationships by itself. There is a workaround for this that we can create some SQL views in Azure side to make it work. This can be an expensive solution. The other way is to load the data warehouse into a Power BI Desktop model which can detect the relationships automatically.

Now you know a bit bout Azure SQL Data Warehouse let’s get back to the subject and talk more about Power BI and Azure SQL Data Warehouse.

First things first. You need to have a Microsoft Azure subscription. If you don’t already have it you can use it for a one month trial here. You’ll also get $250 credit. But, remember that if you succeed the $250 in less than a month then you’ll need to pay for it if you want to use it longer.

Install Azure SQL Data Warehouse

After you get your Azure subscription, login to your account and you should see a dashboard like this

I’m not going to explain the above dashboard as it is out of scope of this article.

Click New

Click “Data + Storage” then click “SQL Data Ware House”

Enter a name for your database
Select a performance value

Continue reading “Azure SQL Data Warehouse and Power BI” →

Update: If you are here to learn how to browse your SSAS Multidimensional model in Power BI please refer to this article. The current article shows you how to refresh data on Power BI service on top of a SSAS Multidimensional instance based on data import scenario.

It’s been a while that lots of us are waiting for seeing improvements on Power BI and SSAS Multidimensional. The good news is that Microsoft released a new version of Power BI Personal Gateway last week on 3 Sep 2015. One of the new features added to this release is that we can now refresh an on-prem SSAS Multidimensional model (data import scenario) after we published it to Power BI website. But, what data import scenario means? That means we cannot create mashups with data we already have in an existing SSAS Multidimensional database/cube through the SQL Server Analysis Services connector which is available on Power BI website. So we need to connect to a SSAS multidimensional instance through Power BI Desktop and load the cube’s data into the Power BI model. Indeed we will create a relational model on top a multidimensional model from SSAS.

Then we can create reports and publish them to Power BI website and finally we’ll be able to schedule data refresh on the Power BI website.

We can also connect to a SSAS Multidimensional instance through Power Pivot AND/OR Power Query from Excel then load the Excel file into Power BI website.

Note: We can do the same through Power Query, but, we won’t able to setup a data refresh schedule on Power BI website if we didn’t load

It’s just awesome isn’t it?

In this post I show you how to implement all the data import scenarios using Power BI Desktop, Power Pivot and Power Query from Excel.

First of all you need to download the gateway from here. Then you need to uninstall the existing version of Power BI Personal Gateway from your machine and install the new version. The whole gateway installation and process of refreshing an on-prem SSAS database is pretty much the same as what I explained in this post so I leave the installation part to you. However, I explain the data refresh part again.

SSAS Multidimensional Data Import Scenario Through Power BI Desktop:

Get Data

Open Power BI Desktop
Click Get Data
Select “SQL Server Analysis Services Database” from the list and click “Connect”

Enter the SQL Server Analysis Services instance name
The database name is optional, but, I put “AdventureWorksDW2012”
Click “Select items and get data from Multidimensional or Tabular model”
As you can see you can also put your MDX or DAX custom queries, but, we leave it blank in our sample
Click OK

Continue reading “Power BI and SSAS Multidimensional” →

Role-playing dimension is one those concepts that is discussed a lot from time to time. I also posted an article about implementing role-playing dimensions in Tabular models.

To recap, in the role playing dimensions in SSAS Tabular article I explained three different solutions:

Importing role playing dimensions several times into the model
Creating database views in the source side (in case your source is a from of RDBMS like SQL Server, Oracle etc…) then import the data into the model
Keep the inactive relationships in the model and create several measures to take care of different roles using USERELATIONSHIP functions in DAX

I this post I explain implementation of the third option above. In this scenario you need to create especial calculated measures based on the roles you have in a fact table. One the most common role-playing dimensions is Date dimension. Consider you have to show Internet Sales Amount by Order Date, Due Date and Ship Date in a single chart in your report. In this case, having 3 different date tables won’t help us to achieve the goal.

New to Power BI? Quickly learn about Data Visualisation in Power BI here.

Defining new Measures in Power BI Desktop

Basically, what I’m going to explain in this post is using inactive relationships between FactInternetSales table and the DimDate dimension by adding a new Calculated measure. In this case, we’ll be able to show Sales Amount by different roles, well, dates in this sample in a single chart.

Continue reading “Side-by-side Role-Playing Dimensions In Power BI” →

Downloading and Installing Power BI Enterprise Gateway

Share this:

What Is Azure SQL Data Warehouse?

Install Azure SQL Data Warehouse

Share this:

SSAS Multidimensional Data Import Scenario Through Power BI Desktop:

Get Data

Share this:

Defining new Measures in Power BI Desktop

Share this: