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101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAdvanced Analytics in Power BI with R and Python $eIngesting, Transforming, Visualizing /$fby Ryan Wade
205   $a1st ed. 2020.
210  1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2020.
215   $a1 online resource (XLVI, 391 p. 84 illus.) 
300   $aIncludes index.
311   $a1-4842-5828-2 
327   $aPart I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python.-7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts. .
330   $aThis easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard to do, if not impossible, using native Power BI tools without Power BI Premium capacity. For example, you will learn to score Power BI data using custom data science models, including powerful models from Microsoft Cognitive Services. The R and Python languages are powerful complements to Power BI. They enable advanced data transformation techniques that are difficult to perform in Power BI in its default configuration, but become easier through the application of data wrangling features that languages such as R and Python support. If you are a BI developer, business analyst, data analyst, or a data scientist who wants to push Power BI and transform it from being just a business intelligence tool into an advanced data analytics tool, then this is the book to help you to do that. You will: Create advanced data visualizations through R using the ggplot2 package Ingest data using R and Python to overcome the limitations of Power Query Apply machine learning models to your data using R and Python Incorporate advanced AI in Power BI via Microsoft Cognitive Services, IBM Watson, and pre-trained models in SQL Server Machine Learning Services Perform string manipulations not otherwise possible in Power BI using R and Python.
606   $aMicrosoft software
606   $aMicrosoft .NET Framework
606   $aQuantitative research
606   $aBig data
606   $aMicrosoft
606   $aData Analysis and Big Data
606   $aBig Data
615  0$aMicrosoft software.
615  0$aMicrosoft .NET Framework.
615  0$aQuantitative research.
615  0$aBig data.
615 14$aMicrosoft.
615 24$aData Analysis and Big Data.
615 24$aBig Data.
676   $a001.4226028566 
700   $aWade$b Ryan$0859869
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910427050203321
996   $aAdvanced analytics in power BI with R and Python$91918799
997   $aUNINA