Dejan Sarka, MCT and SQL Server MVP, is an independent trainer and consultant that focuses on development of database and business intelligence applications. Besides projects, he spends about half of the time on training and mentoring. He is the founder of the Slovenian SQL Server and .NET Users Group. Dejan Sarka is the main author or co-author of sixteen books about databases and SQL Server. Dejan Sarka has also developed many courses and seminars for Microsoft, SolidQ, and Pluralsight.
Data Science in Power BI Desktop
- Stopnja 400
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Datum
sreda
22. maj 2019 08:20
Two of the most popular modern topics are data science and Power BI. The nice thing is that you can easily combine both of them by including data science analyses in Power BI. You can do this in numerous ways. Many Power BI visualizations already include the Analytics tab with plethora of intermediate-level analytical functions available. For example, you can add a trend line and many other lines to the Scatter chart. You can use R and / or Python script sources. You can do the whole analysis in R or Python, and then visualize the results in Power BI. You can also use the good old SSAS Multidimensional Data Mining as the source. You can include Azure ML predictions in a Power BI model. With R and Python visuals, you can add the impressive visualizations from these two languages in a Power BI report and dashboard. You can also use R and Python in Power Query for advanced data manipulation. There are also many custom visuals that include data science analyses. This session introduces all of the mentioned options and shows some really advanced reports done inside Power BI.