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Power BI Publish to Web for Anonymous Access is Here

Earlier this week on Wednesday the Microsoft Power BI made an incredibly exciting announcement and released Power BI “publish to web” as a preview feature. This is HUUUUGE news! This was probably the top requested feature and its finally here thanks to the hard work and dedication of the Microsoft Power BI team!

Read Getting Started with R Visuals in Power BI

Power BI “publish to web” allows you to easily expose a Power BI report to the world through an iframe that can be embedded wherever you like.

To publish your Power BI report to the web, log into your Power BI site.

Find the report that you want to share and click File in the top left.
Power BI publish to web

You’ll see a message pop up box similar to below. Click the yellow button to create the embed code.
Power BI publish to web preview

This is where you’ll see a very important warning!
WARNING: Reports that you expose through the “publish to web” feature will be visible to everyone on the internet! This means NO AUTHENTICATION is required to view the report that is embedded in your application.
warning 2

Once you do that, you’ll receive an embed code that you can then use to expose your Power BI report within your blog as seen below!

https://msit.powerbi.com/view?r=eyJrIjoiYTNjNzcwNjctNTczMy00ZDMxLWFlMGUtMDViODA1NGZiNmI0IiwidCI6IjcyZjk4OGJmLTg2ZjEtNDFhZi05MWFiLTJkN2NkMDExZGI0NyIsImMiOjV9

As you can see the report maintains all the interactivity features of Power BI. And as your Power BI report updates and changes, those changes will be reflected in your embedded Power BI reports!

Pretty awesome!

Additional Resources

Read the Power BI “publish to web” announcement here.

Read the Power BI “publish to web” documentation here.

Feedback

Let me know what you think of this feature or if you have any questions. Leave a comment down below.


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MDX NON EMPTY KEYWORD VS NONEMPTY FUNCTION

Non Empty vs NonEmpty

Hey everyone, in this blog I want to address a very common MDX Question. What is the difference between the NON EMPTY keyword and NONEMPTY function? To take it a step further which one should you use?

Non Empty keyword VS NONEMPTY Function.

The big difference between the NON EMPTY keyword and the NONEMPTY function is when the evaluation occurs in the MDX. The NON EMPTY keyword is the last thing that is evaluated, in other words after all axes have been evaluated then the NON EMPTY keyword is executed to remove any empty space from the final result set. The NONEMPTY function is evaluated when the specific axis is evaluated.

Should I use NON EMPTY keyword or NONEMPTY function?

Ok Mitchell, so you told me when each of these are evaluated but really you haven’t told me anything up until this point. Can you tell me which one I should use already? Well, unfortunately, it depends. Let’s walk through an example of each using the BOTTOMCOUNT function.

BOTTOMCOUNT FUNCTION with NON EMPTY Keyword

In this example I’m returning the bottom ten selling products for internet sales. Notice that I have returned all products that have no internet sales, this is not necessarily a bad thing, maybe you want to return products that don’t have sales.

image

However if you don’t want to return these products then we can try using the NON EMPTY keyword. In the below example you can see the results when I add NON EMPTY to the ROWS axis.

image

WHOOOAAA, what happened?? A lot of people would have expected the results here to show the bottom ten products that DID have sales. However, that is not the case, remember that I said the NON EMPTY keyword is evaluated LAST after all axes have been evaluated. This means that first the bottom ten selling products which have $0 in sales are first returned and then the NON EMPTY keyword removes all that empty space from the final result.

BOTTOMCOUNT function with NONEMPTY function.

So let’s try this again, if you want to return the bottom ten products that had sales then we must first remove the empty space before using the BottomCount function. Take a look at the code below:

image

In this code we first remove the empty space before using the BOTTOMCOUNT function. The result is we return the bottom ten products that had internet sales. Once again neither one is right or wrong here it just depends on what you want in your final result.

NON EMPTY Keyword vs. NONEMPTY Function – Performance

There is a very common misconception that the NONEM

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Extracting Data From Multiple Files with Power Query

  • 13 August 2013
  • Author: DevinKnight
  • Number of views: 5936
  • 0 Comments

In this post I’d like to demonstrate another way Power Query can solve simple data extraction problems without much time or effort.  If you’re still learning the basics of Power Query please refer back to an earlier post here.

This demonstration will show you how to use Power Query to scan a file folder to search for a set of files to load.  Then load the contents of multiple files all at once and use transformations to format the data appropriately..

Step by Step

  • Launch Excel 2010 or higher.
  • Select the Power Query tab.
  • Select From File under the Get External Data section of the tab.
  • Choose the option From Folder, which allows you to load more than one file at once.

image

  • Browse to a folder, which has the files you desire to load then click OK. These files should all be formatted similarly to each other.  Having the same data types and column names.

image

  • This opens the Query Editor, which lists all the files that are available in the folder you selected in the previous step.  The initial view show metadata about the files like the file name, extension, relevant dates and the folder path.  If there were other files in this folder that should not be loaded you could filter them out at this point.  The other interesting columns are Content and Attributes.  The Attributes column  has additional metadata that can be queried and the Content column stores the actual data of each file.  Click the down arrows next to the column header for Content. 

image

  • The data from all four files in now combined together into a single query, but there is still transformations in the data that must be completed.  Start by right-clicking on Column1 header and select Split Column > By Delimiter.

image

  • Click OK to accept the defaults of configuration, which will split each column by a comma.
  • Next, right-click on either column header and select Use First Row As Headers to give the query appropriate column names.

image

  • You will notice the previous step only gave us column headers from the first file.  If you look in the results you will find the column headers listed for the other files too.  To remove these extra column header rows select the down arrow next to the Name column and uncheck the Name value then click OK.

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  • You have now successfully combined 3 files using Power Query.  Click Done to bring this data into Excel.  Once in Excel this can easily be added to tools like Power Pivot for additional analysis.

Hope this helps!

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DevinKnight

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