In many corporations depending on the type of data is being used there could be different types of the sensitivities that should be applied to that data. Data Classification fulfills in Power BI Service this matter very easily. In today’s post you’ll learn how to setup Data Classification in Power BI Service.
First of all I want to inform you that Data Classification is NOT a sort of security or privacy setting. It is only a TAG which is all about informing Power BI users across a corporation to take extra care when they want to share data with other people inside or outside of that corporation. For instance some data might be OK to be shared externally outside the company, but, the other data might not be shared with groups of people even within that corporation.
Depending on your corporation you might have different levels of sensitivity like
High Sensitive Data
Medium Sensitive Data
Low Sensitive Data
So depending on what level of sensitivity, for instance for High Sensitive Data, the Power BI users should be really careful of who they share Power BI Dashboards and data with. In Power BI Service we can easily setup data classification on our dashboards so anyone who is looking at that dashboard is able to understand how sensitive that dashboard is and who they can share it with.
To be able to setup Data Classification in Power BI Service you have to:
In case that you want to add another admin user,and if you already integrated your on-premises Active Directory with Azure Active Directory (AD) then you can either grant necessary admin rights to that user from your Azure portal in Azure AD or directly from Office 365 Admin Centre.
The user needs to be an Office 365 “Global Administrator” to be able to setup data classification in Power BI Service. A global administrator will have access to “Admin Portal” panel within Power BI Service which includes data classification and many more other important settings.
Make a User Global Administrator in Office 365
After you signed into your Power BI Service account,
In the previous posts, here and here, I explained how you can use Power BI Desktop Query Parameters for many different use cases. Power BI development team added another cool feature to Power BI Desktop on July 2016 which is the ability to add a List Query output to a query parameter as it’s “Suggested Values” (formerly “Allowed Values”). This feature is very useful and from now on we are not restricted to proviode a static list of values in “Manage Parameters”. In this post I show you how to use a list output in query parameters.
Note: This feature is NOT available in DirectQuery mode at the time of writing this post.
In this post as usual I’ll connect to a SQL Server database as a sample. To be able to follow this post you have to have:
In the first post of these series I explained how to create dynamic data sources using Query Parameters. You also learnt how to use Query Parameters in Filter Rows. But, what if we want to filter query results based on the values of a column from a particular table? Previously we couldn’t answer these sort of questions if we want to filter FactInternetSales based on a selected values of EnglishProductName column from DimProductCategories using Query Parameters. But, now we can easily implement those sort of scenarios.
Let’s implement this scenario.
Loading Data into the Model:
Open Power BI Desktop
Get data from SQL Server and connect to Adventure Works DW 2016 CTP3
Select “FactInternetSales”, “DimProduct”, “DimProductSubCategory” and “DimProductCategory” tables then click “Load”
Switch to “Relationships” view to make sure the relationships detected correctly then click “Edit Queries” from the ribbon
A while ago I wrote a blog post about Azure SQL Data Warehouse and Power BI which I explained how to install a new instance of Azure SQL Data Warehouse and how to visualise your Azure SQL DW data in Power BI. In this post I explain how to query an Azure SQL DW in SSMS and Visual Studio.
An existing instance of an Azure SQL Data Warehouse. If you don’t have an existing one check this out
Querying Azure SQL Data Warehouse from Visual Studio
Prior the latest release of SQL Server Management Studio (SSMS) 2016, the only available tool for querying an Azure SQL Data Warehouse was SQL Server Data Tools (SSDT) for Visual Studio 2013 or 2015. Here is how you can use SSDT 2015 to query an Azure SQL Data Warehouse:
Open SQL Server Data Tools 2015
Click “SQL Object Explorer” from View menu
Click “Add SQL Server”
Enter “Server Name”
If you don’t recall server name then open a web browser and log into Azure portal
Click “SQL databases”
Click any desired Azure SQL Data Warehouse you created before. Make sure the database is “Online”
A while ago I wrote a blog post about Power BI Publisher for Excel. Today I want to explain some new features added to the publisher. In this post you learn how to analyse Power BI data in Excel. Using the new Power BI Publisher for Excel, not only can we pin an Excel range or chart to a Power BI dashboard directly from Excel, but also we are now able to easily connect to a Power BI service, select any group workspaces and analyse a desired report or dataset.
Desktop versions of Microsoft Excel 2007 and later
Power BI Publisher for Excel add-in will be enabled by default after you install it, however, if you don’t see the “Power BI” tab in the ribbon in Excel you can enable it from File –> Options –> Add-ins –> COM Add-ins –> tick Microsoft Publisher for Excel.
Connect to and Analyse Power BI Data in Excel
Analyse Power BI Service Reports or Datasets in Excel (From Power BI Service)
Previously we could analyse Power BI data in Excel directly from Power BI service by:
Log in to Power BI Service
Clicking ellipsis button of a desired dataset and clicking “Analyse in Excel”
Clicking ellipsis button of a desired report and clicking “Analyse in Excel”
Doing either way, it downloads an “odc” file that could be opened in Excel.
Now you can analyse the data in Excel using pivot tables and pivot charts.
One of the most powerful features in Power BI and Excel is supporting geospatial visualisations. In Excel we can use Map visualisation in Power View, or use Power Map directly. In Power BI, as you know, there are two built-in visualisations supporting geographic coordinate data, Map and Filled map. They work beautifully if you have enough data supported by Bing Maps. But, there are some issues with Map visualisations in both Power BI and Excel. In this post I address some of the issues I faced myself and I’ll provide the solutions for the issues. As “Filled Map” and “Map” visualisations in Power BI are very similar my focus in this post would be on “Map” visualisation. My intention is not explaining Power View and Power Map that much so my focus in this article would be on Power BI more than the other two.
To experiment everything I explain in this post you need to have:
The new SQL Server sample, WideWorldImportersDW (WWI). You can download it here
The latest version on Power BI Desktop (current version is 2.35.4399.381 64-bit (May 2016))
Select Fact.Sales and Dimension.City then load data
Map Issues In Power BI
Wrong Cities in Power BI
Expand the “Dimension City” table
Select “City” column then change its Data Category to City (Data Category is on “Modeling” tab from the ribbon)
Put a Map visual into the page
Put “City” on Location
Put “Total Excluding Tax” on Size
As you see sales distributed across different countries, but, this is not quiet right.
Put a slicer on the page then put “Country” on the slicer
Click “United States” to filter the Map
Oops! This is not quiet right. What happened is that Bing Map Engine gets confused with the city names so that it shows a city with the same name outside of the US, just like New Plymouth which a city in New Zealand, but, the New Plymouth we have in our data source is the New Plymouth from Idaho in the US.
Have you created a robust model in Power BI Desktop and you are looking for a way to import it to an instance of SQL Server Analysis Services Tabular? Hmm, it would be highly beneficial if you could import Power BI model to SSAS Tabular and it potentially saves lots of development time and costs. The good news is that with SQL Server 2016 and SQL Server Data Tools for Visual Studio 2015 it is possible. In this post I show you how to import Power BI Desktop model to SSAS Tabular 2016. Unfortunately, you cannot do the job in any prior versions of SQL Server, SQL Server Management Studio or SSDT.