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000944894 1001_ $$aWade, Ryan.
000944894 24510 $$aAdvanced analytics in Power BI with R and Python :$$bingesting, transforming, visualizing.
000944894 260__ $$a[Place of publication not identified]$$bAPRESS,$$c2020.
000944894 300__ $$a1 online resource
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000944894 5050_ $$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. 
000944894 506__ $$aAccess limited to authorized users.
000944894 520__ $$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.
000944894 650_0 $$aMicrosoft software.
000944894 650_0 $$aMicrosoft .NET Framework.
000944894 650_0 $$aBig data.
000944894 77608 $$iPrint version: $$z1484258282$$z9781484258286$$w(OCoLC)1138673483
000944894 852__ $$bebk
000944894 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-1-4842-5829-3$$zOnline Access$$91397441.1
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