Advanced Analytics in Power Bi with R and Python: Ingesting, Transforming, Visualizing

Wade, Ryan

  • 出版商: Apress
  • 出版日期: 2020-10-13
  • 定價: $1,800
  • 售價: 8.0$1,440
  • 語言: 英文
  • 頁數: 393
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484258282
  • ISBN-13: 9781484258286
  • 相關分類: Power BIPython程式語言R 語言
  • 立即出貨 (庫存=1)

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商品描述

This 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.

What You Will Learn

  • 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


Who This Book Is For
Power users, data analysts, and data scientists who want to go beyond Power BI's built-in functionality to create advanced visualizations, transform data in ways not otherwise supported, and automate data ingestion from sources such as SQL Server and Excel in a more succinct way

商品描述(中文翻譯)

這本易於理解的指南提供了R和Python的技巧,幫助您學習並應用於Microsoft Power BI的領域中的頂尖語言。數據分析專家和作者Ryan Wade向您展示如何使用R和Python執行在沒有Power BI Premium容量的情況下,使用原生Power BI工具幾乎不可能完成的任務。例如,您將學習使用自定義數據科學模型對Power BI數據進行評分,包括來自Microsoft Cognitive Services的強大模型。

R和Python語言是Power BI的強大補充。它們提供了高級數據轉換技術,這些技術在Power BI的默認配置中很難實現,但通過R和Python等語言支持的數據整理功能變得更加容易。如果您是BI開發人員、業務分析師、數據分析師或想將Power BI從僅僅是商業智能工具轉變為高級數據分析工具的數據科學家,那麼這本書將幫助您實現這一目標。

您將學到以下內容:
- 使用ggplot2套件在R中創建高級數據可視化
- 使用R和Python導入數據,克服Power Query的限制
- 使用R和Python對數據應用機器學習模型
- 通過Microsoft Cognitive Services、IBM Watson和SQL Server Machine Learning Services中的預訓練模型,在Power BI中整合高級人工智能
- 使用R和Python執行Power BI中無法實現的字符串操作

這本書適合以下讀者:
- 高級用戶、數據分析師和數據科學家,希望超越Power BI內建功能,創建高級可視化效果,以不支持的方式轉換數據,並以更簡潔的方式自動從SQL Server和Excel等來源進行數據導入。

作者簡介

Ryan Wade is a data analytic professional with over 20 years of experience. His education and work experience enable him to have a holistic view of analytics from a technical and business viewpoint. He has an MCSE with an emphasis on BI reporting and Microsoft R. He has an advanced understanding of R, Python, DAX, T-SQL, M, and VBA. He knows how to leverage those programming languages for on-premise and cloud-based data analytics solutions using the Microsoft Data Platform.

Ryan is a data analytics enthusiast and has spoken at R meetups, Python meetups, SQLSaturdays, TDWI Conference, and PASS Summit about various data analytics topics. He is the developer of a comprehensive online course for ExcelTv showing how to implement R in Power BI for advanced data analytics and data visualization.

 

作者簡介(中文翻譯)

Ryan Wade 是一位擁有超過20年經驗的數據分析專業人士。他的教育和工作經驗使他能夠從技術和業務的角度全面了解分析。他擁有以商業智能報告和Microsoft R為重點的MCSE學位。他對R、Python、DAX、T-SQL、M和VBA有深入的理解。他知道如何利用這些程式語言在本地和基於雲的數據分析解決方案中使用Microsoft數據平台。

Ryan 是一位數據分析愛好者,曾在R meetups、Python meetups、SQLSaturdays、TDWI Conference和PASS Summit上就各種數據分析主題發表演講。他是ExcelTv的一個全面線上課程的開發者,該課程展示了如何在Power BI中實施R進行高級數據分析和數據可視化。