Introduction: Azure Machine Learning Studio is an amazing tool that lets us create efficient ML experiments with simple drag and drop features. We can predict anything from Flight Predictions to Churn Analysis. But what if we want to represent this predicted data a more visually appealing format? Well it is possible to do this by representing your predictions on Power BI! Pre-Requisites: Basic Understanding of Azure Machine Learning Studio. Basic Understanding of Power BI. A Blob Container created on Azure Storage.   Steps: Create your Azure Machine Learning Experiment on Azure Machine Learning Studio. Convert your Training Experiment to a Predictive Experiment and Deploy it as a Web Service. We will create a Console application in Visual Studio and copy paste the code inside Batch Execution. For automation we can create automated data pipelines but for now we will just use a simple Console application. Remove the existing code from the Console Application and copy paste the Batch Execution code. Install the necessary Nuget Packages and also update the following parameters. – BaseURL will be the same. – Storage Account Name, Storage Account Key and Storage Container Name will be parameters that can be found in your Azure Blob Storage which was created. – Api Key can be found in the Web Experiment Page in Azure Machine Learning Studio. – The input path is the path where you have saved your input csvfile for Batch Execution. Your Input csv file should have all the features which you have used to train your experiment After you run your Console application a new output1results.csv file should get generated in your Blob Container. The output results should include the labels which your experiment generates in it’s output. It should include the Scored Labels and Scored Probabilities labels as well. Now you can get your data using Azure Blob Storage as your source in Power BI and use the columns in the output1result.csv file to generate your ML Predicted Reports. The Report can look something like this. I hope this blog helps you to combine Azure Machine Learning Studio and Power BI to create a powerful predictive solution.

Introduction: Narratives for Power BI is a product that automatically delivers dynamic narratives that explain the insights within your data. No more manually writing explanations and spending time interpreting data. Instead, the narratives, which are powered by advanced analytics, are perceptive and dynamic and explain what is most interesting and important in your data. Drill down deeper into your data and watch narratives update in real-time during the data discovery process Steps: Go to powerbi.narrativescience.com and enter your business email id.  A link for downloading the extension and installation instructions will be mailed to you A pibiviz file will be downloaded on downloading the extension. A pbiviz file is nothing but a custom visual which can be imported in Power BI Desktop. Import the file on Power BI Desktop Benefits: Automated Narratives generated that give more detailed insights about the report which may not even be obvious Real time update on interaction with data Many customization options to personalize your narrative Click on Narrative and select Dimensions and Values based on which Narratives will be generated. After selecting the fields you will have to select your narrative type. Discrete: For distinct data like that in Bar Charts Continuous: For continuous data like that in Line Charts Percent of Whole: For data by percentage like Pie Charts Scatterplot: For data based on scatterplot like Charts A narrative gets generated It also changes on real time interaction The type structure and verbosity can be customized in the Format Pane Type Can be Discrete, Continuous, Percent of Whole or Scatterplot. Structure can be either in Paragraph format or Bullet Points. Verbosity the level of information displayed. Low verbosity would show less detailed narrative with high level information while High verbosity would show a very detailed narrative. Medium verbosity would be a midway between both. I hope this blog encourages you to use this powerful extension to improve your reports by making it as detailed as possible with minimalistic efforts!  

Introduction: Power BI comes with a powerful language recognition engine that lets you ask questions of your data using conversational phrases and questions. Based on these questions, Power BI dynamically creates charts and graphs. For example, if the data is defined as a date type, it is more likely to be displayed as a line chart. Data that is categorized as a city is more likely to be displayed as a map. Questions can be asked on a dashboard. The feature is called as Q&A or Questions & Answers. Natural Language Q&A is really an underused tool in Power BI despite of being really powerful. Following is my dashboard on a Credit Card transaction dataset. I will be performing simple Q&A questions on this dashboard. Pre-Requisites: Power BI Subscription Features of Q&A: Auto Prompts: This prompts are created on the basis of: a. the questions used to create tiles that are already pinned to the dashboard, and b. the name of tables in the underlying dataset(s). Can build a question using the prompts (Eg. What is the total amount in April) Dropdown pops up while typing a question. Helps with auto-replacement terms as well. Can use Aliasing table to make querying more powerful. Featured Q&A Questions Click on your Dashboards Ellipses and then select Settings. Click on the Datasets tab and select Featured Q&A questions. Select Add a question and type a question and then click on Apply. Now whenever a user starts typing on Q&A they will be prompted with this question first. Dims words it does not understand. Can combine results from more than one data set. When you type a query, Power BI looks for an answer in any dataset that has a tile on that dashboard.  If all the tiles are from datasetA, then your answer will come from datasetA.  If there are tiles from datasetAand datasetB, then Q&A will search for the best answer from those 2 datasets. Dynamically generates a visual depending on the question. Can change the visual type using the ‘as’ keyword. Can pin this new visualization back to your dashboard. The visual answers can also be edited. Just by using the Visualizations and the Filter panes on the right side of the screen we can alter the layout, adjust filters and change fields. Conclusion: We have discussed the various features that can be used with Q&A which can improve our ability in analyzing data.  

Introduction: In this blog we will discuss the different Power BI Premium Capacity nodes available and the steps to purchase these. We will also discuss how to assign a premium node to a workspace in Power BI. Power BI Capacity Based SKUs: There are 3 categories of SKUs that can be purchased which gives us a number of ways to embed our content using any of the capacities depending on our requirement. Following are the 3 different series provided by Microsoft. Power BI Embedded A SKUs This capacity is generally used by small ISVs for embedding own solutions. Unlike the other two series this series is charged on an hourly basis. It can be paused and started whenever needed and also it has additional scalability. Power BI Premium EM SKUs This capacity is also generally used by ISVs for 3rd party embedding in a custom application or in SaaS applications like Sharepoint or Teams. It offers everything provided by A SKUs and also offers the ability to share Power BI reports. EM SKUs unlike A SKUs cannot be paused and require a monthly or annual commitment. Power BI Premium P SKUs For this capacity, the hosting organization does not generally have any requirement for custom software development. It has all the features of E SKUs and also additional Power BI services like App sharing, Ad hoc dashboard sharing.etc. They allow the users to use Power BI’s browser based experience and are more dependent on the UI provided by Power BI. Purchasing the nodes: If you are a Billing Admin in your O365 tenant then you can purchase the capacity nodes under Purchase service in Billing. Currently the EM3, P1, P2 and P3 capacities can be purchased from the Office portal. The A series can be purchased from the Microsoft Azure Portal. Click on New and search for Power BI Embedded. Fill in the necessary details. A capacity administrator needs to be assigned, who will be responsible for creating the capacities and assigning it to the workspaces. Note: I still haven’t figured out where to find the EM1 and EM2 nodes but I’m presuming that they haven’t been released yet. Assigning a Capacity to a workspace: I am using the A1 node for this example. We can see that the Pause feature is available in this node. The first step is that the capacity admin logs into their Power BI account. It is important to note that the capacity admin should have a Pro License. Click on Settings and go to the Admin Portal. Next Select your capacity. Here we can manage capacity size, assign user permissions. etc. If you are opening the portal for the first time then there will be an Assign Workspace option available. Under User Permissions select Entire organization (Assign capacity to entire organization) or Specific users (Assign capacity to specific Users) Depending on the option selected above either the workspaces of the entire organization or the workspaces of the selected users will be loaded below Now we create a sample App workspace named ‘Test Workspace’ to which we will assign our capacity node. You can also use an existing workspace instead. Click on Workspaces and select Create app workspace Name your workspace and enter all the workspace members. Under the Advanced option there should be a Premium toggle button available(This option will only be available if the user is a Capacity Admin, Power BI Admin or a Global Admin and also the User permission mentioned above needs to be given). Turn the Premium option On. Click on Save. If you are using an existing workspace then go to workspace and click on the ellipses(…) beside the workspace and select the Edit Workspace option and enable the Premium option. To be sure that we have successfully backed our workspace with a capacity node, we can confirm by looking at the diamond icon beside our workspace name. Conclusion: We have successfully learnt how to purchase a Power BI capacity node and assign it to a workspace which will enjoy all the benefits provided by Power BI Premium and also give us Embedding Services with it.

Introduction: There may arise a situation where we may want to link one report to a more detailed report dynamically in Power BI. Although we can link dashboards to reports and also provide a custom link for a tile in a dashboard, report to report linkage is currently not a feature available in Power BI. There is a way to achieve this by using URL filtering. Below is a report which shows Card transaction details based on Expense Type. We want to link this report to a more detailed report after clicking on the URL link icons in the table. You can download the sample CSV file from here http://bit.ly/nitincsv1 After clicking on the URL Link icon a report like this should open up which is filtered by Expenditure Type. Steps: The steps to achieve this are mentioned below: 1. We first need to understand how URL filtering works. The syntax for URL filtering is URL?filter=Table/Field eq ‘value’ • Table and Field names are case sensitive • Value should be put in single quotes The Table and Field can be found under Fields in Power BI Desktop The URL can be found on the web page in Power BI Online. Every page in a report has a unique URL in Power BI.  You can find it in the browser address bar of the report. The URL filter for filtering ExpType in CardDetails for the value ‘Bills’ would be, https://app.powerbi.com/groups/me/reports/6ea11c00-85ca-4b8e-907a-42979eaadcaa/ReportSection1?filter=CardDetails/ExpType eq ‘Bills’ 2. The above is a very static example for filtering ExpType but this can be made much more dynamic by using DAX Create a new Calculated Colum for CardDetails   3. Enter the following line as the DAX Code: Link = “https://app.powerbi.com/groups/me/reports/6ea11c00-85ca-4b8e-907a-42979eaadcaa/ReportSection1?filter=CardDetails%252FExpType%20eq%20%27″&CardDetails[ExpType]&”%27” In the above function we have put the ASCII values for blanks, apostrophes and equal to sign for ensuring that the URL works efficiently • Blank -> %20 • Equal -> %252 • Apostrophe -> %27 We append the CardDetails[ExpType] in place of value in the URL Syntax. The rest of the URL remains the same. After pressing Enter the column generated will look something like this in a table visualization 4. The String generated in our column needs to be converted into a hyperlink. Click on Link in Fields, Go to Modeling and select Data Category as Web URL The Link Column should now look like this, 5. We can convert the hyperlink into a more pleasant URL link icon by going to Visualizations->Format->Values->URL Icon(Turn On) 6. The final Report generated looks like this 7. Clicking on the URL icon will dynamically filter a new detailed report in a new tab in your browser. To confirm whether the report has been filtered or not, we can look at the Filters section in Power BI Online as well as the URL. Conclusion: As you can see, we have successfully created a Report with Links which on being clicked generates a detailed report with dynamic filtering.