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My Online Training Hub. Webinar LOGIN. A simple experiment in Machine Learning Studio. If you've never used Azure Machine Learning Studio before, this tutorial is for you.

A simple experiment in Machine Learning Studio

In this tutorial, we'll walk through how to use Studio for the first time to create a machine learning experiment. The experiment will test an analytical model that predicts the price of an automobile based on different variables such as make and technical specifications. Note This tutorial shows you the basics of how to drag-and-drop modules onto your experiment, connect them together, run the experiment, and look at the results.

We're not going to discuss the general topic of machine learning or how to select and use the 100+ built-in algorithms and data manipulation modules included in Studio. If you're new to machine learning, the video series Data Science for Beginners might be a good place to start. If you're familiar with machine learning, but you're looking for more general information about Machine Learning Studio, and the machine learning algorithms it contains, here are some good resources: Tip.

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Power BI publisher for Excel. With Microsoft Power BI publisher for Excel, you can take snapshots of your most important insights in Excel, like PivotTables, charts, and ranges and pin them to dashboards in Power BI.

Power BI publisher for Excel

What can you pin? Just about anything in an Excel worksheet. You can select a range of cells from a simple sheet or table, a PivotTable or PivotChart, illustrations and images, text. What you can't pin: you cannot pin 3D Maps or visualizations in Power View sheets. There are also some elements you can pin, but it wouldn't make much sense to, like a Slicer or Timeline filter. Microsoft Power BI.

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Gartner Reprint. Published: 10 March 2016 ID: G00278437 Analyst(s): Cindi Howson, Josh Parenteau, Rita L.

Gartner Reprint

Sallam, Thomas W. Oestreich, Joao Tapadinhas, Kurt Schlegel Summary The BI market has shifted to more user-driven, agile development of visual, interactive dashboards with data from a broader range of sources. Overview Key Findings The business intelligence (BI) and analytics market has passed a tipping point as it shifts away from IT-centric, reporting-based platforms and toward modern BI and analytics platforms that enable smarter analytics and greater agility. Recommendations. Power BI. SQLBI - Marco Russo. I am so happy to announce that The Definitive Guide to DAX is finally available!

SQLBI - Marco Russo

I and Alberto Ferrari spent one year writing this book, and several years collecting the knowledge necessary to do that. The complete title is The Definitive Guide to DAX: Business intelligence with Microsoft Excel, SQL Server Analysis Services, and Power BI. You can imagine why we like to shorten it! However, the complete title gives you an important hint: this book cover the new DAX syntax of Excel 2016, Power BI Desktop, and Analysis Services 2016.

For example, we covered all table functions useful for calculated tables, which is a feature released in Power BI Desktop after we completed the book writing. But everything has a cost. What if you are a DAX beginner? Why am I so excited about this book? After this self-celebration, let me spend some paragraph about the content. Topics in chapters 1 to 12 are covered in our Mastering DAX workshop. Have a nice reading!

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Going Hardcore on your Business Intelligence with Power BI - Adam Cogan. Real-Time Analytics with Azure and Power BI. I love Sunday nights.

Real-Time Analytics with Azure and Power BI

Nice breeze flowing through the open windows, crickets chirping, pups resting, social networks are slower paced and email is still fairly quiet while Redmond is enjoying the end of their weekend. After starting a new healthy diet and exercise plan, I am craving sinful food and need to keep myself distracted. Playing with data and continuing on with the Exploring Oceans of Data series should keep me from going near that refrigerator in my kitchen tonight.

This week I will share how to design a real-time analytics solution using Azure Event Hubs, Stream Analytics and Power BI. This combination is one of few different real-time cloud analytics options with Azure and Power BI. Solution Overview Azure Event Hubs is an impressive, highly scalable service for ingesting Internet of Things (IoT) event processing data sources. Stream Analytics is great for querying live data streams like Twitter. Putting it Together Another Cool Idea. Using Real-Time Social Media Data with Power BI. Tutorial: Facebook analytics using Power BI Desktop. Tutorial: Facebook analytics using Power BI Desktop In this tutorial you learn how to import and visualize data from Facebook.

Tutorial: Facebook analytics using Power BI Desktop

During the tutorial you'll learn how to connect to a specific Facebook page (the Power BI page), apply data transformation steps, and create some visualizations. Here are the steps you'll take: Task 1: Connect to a Facebook PageTask 2: Create visualizations using the Report view Step 1: Create a Treemap visualizationTask 3: Shape data in the Query view Step 1: Split the date-time column into two Step 2: Add an aggregate value from a related tableTask 4: Create additional visualizations using the Report view Step 1: Load the query to your report Step 2: Create a Line chart and a Bar chart.

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