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從數據處理到資料視覺化-商業智慧的實作與應用

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在這份投影片中,首先介紹商業智慧簡介及企業內部數據決策的流程,並使用一個例子呈現從數據處理到資料視覺化的實作。

讓對資料科學及人工智慧有興趣的同好了解資料處理及商業智慧的應用。

Publicado en: Datos y análisis
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從數據處理到資料視覺化-商業智慧的實作與應用

  1. 1. 從數據處理到資料視覺化— 商業智慧的實作與運用 OPEN LIVING 樂活共生實驗基地 » Pei-Syuan » 2018/12/8
  2. 2. Outline » Business Intelligence » 企業內部數據決策 » 呈現視覺化報表的步驟 » R » Power BI » Data Cleaning » Data Preprocessing » Data Visualization 2
  3. 3. Business Intelligence 3  Source: http://www.jandhconsulting.net/business-intelligence-bi-en.html
  4. 4. 企業內部數據決策 4 數據處理 <-數據處理  Source: https://medium.com/@Echo.C/%E4%B8%80%E5%80%8B%E9%97%9C%E6%96%BC%E6%A3 %97%E5%AD%90%E6%A0%B8%E6%A1%83%E7%9A%84-meetup- %E5%88%86%E4%BA%AB-b5c55b78421f
  5. 5. What I am doing now 5 數據處理IT: 資料庫  Source: https://medium.com/@Echo.C/%E4%B8%80%E5%80%8B%E9%97%9C%E6%96%BC%E6%A3 %97%E5%AD%90%E6%A0%B8%E6%A1%83%E7%9A%84-meetup- %E5%88%86%E4%BA%AB-b5c55b78421f
  6. 6. 6  Source: iThome,用資料科學發現與解決企業所不知道的各種問題 http://www.ithome.com.tw/tech/86091
  7. 7. 7 Data Engineer Software Engineer Data Analyst Data Scientist Domain Expert  Source:經理人,「大數據」到底與我有什麼關聯 https://www.managertoday.com.tw/articles/view/52306
  8. 8. Roles in a Data Science Project 8  Source: https://www.slideshare.net/emcacademics/building-data-science-teams-31057129
  9. 9. When a new request has been proposed? New Request » Discuss with users » What is the motivation? » How to deploy? 9
  10. 10. 呈現視覺化報表的步驟 10 Data visualization Data preprocess Data cleaning Understand motivations and Data Make features 20% 30% 30% 20%
  11. 11. R 11
  12. 12. R or Python » 主要用於統計分析、繪圖、 資料探勘 12  Source: Python V.S R語言?在數據分析與挖掘方面該選哪一個? https://www.itread01.com/articles/1475545480.html
  13. 13. Power BI 13
  14. 14. Power BI 14  Source: https://www.zhihu.com/question/35324481 Power BI Service Power BI Mobile » Microsoft Excel add-ins: Power Query, Power Pivot, Power View and Power Map » Microsoft released Power BI on 2015 and can be opened in Excel 2016 » Power BI is a suite of business analytics tools that deliver insights
  15. 15. 15 Power BI Report Server (Free)
  16. 16. Example in Power BI Desktop  [Sample] Retail Analysis 16  Power BI 的零售分析範例教學 https://docs.microsoft.com/zh-tw/power-bi/sample-retail-analysis Relationships Report
  17. 17. Power BI Visuals 17  Source: https://www.sqlbi.com/wp- content/uploads/videotrainings/dashboarddesig n/visuals-reference-may2017-A3.pdf
  18. 18. 情境 18
  19. 19. 情境 » 如果你有很多不同天的價錢資料, 要如何呈現 成視覺化圖表? » 使用者需求? 製作報表的目的及目標? 19
  20. 20. Data you have » Brand: ABC, XYZ » Date: 2018/11/5~2018/11/30 » Model: A48a1, A50a2, A65a1, A65b1, X43y2, A50x1, X50x4, X65x3 » Other attributes: Size, Type, Price, LAN 20
  21. 21. I. Understand motivations and Data » 目的: 比較不同品牌的價錢變化 » 時間區間以天為單位? 以周為單位? » 每一個Model, 每周有5~7個價錢, 要取最大值, 最小值, 還是平均值? 21 # of rows: 208 # of columns: 8
  22. 22. Import library {} 22 I. Understand motivations and Data Import Data » 比對字串是不是有符合正確的格式
  23. 23. Data cleaning 23
  24. 24. II. Data cleaning 24 Data type » Text » Date » String » Numeric Data modeling » Outlier » Missing value » Standardization
  25. 25. Regular expression 正則表示式 » 比對字串是不是有符合正確的格式 25  [系列活動] Python爬蟲實戰 https://www.slideshare.net/tw_dsconf/python-78691041
  26. 26. II. Data cleaning Model » 將model_original清理成單純的model名稱 {library: magrittr, stringr, purrr} 26 分解步驟
  27. 27. 27 Model » 將model_original清理成單純的model名稱 {library: magrittr, stringr, purrr} II. Data cleaning
  28. 28. III. Data Preprocessing 28 Make features » (1) 定義時間相關欄位 Date -> Week; Month ; Quarter [下頁範例] Date -> Week; Week -> Month ; Month -> Quarter » (2) 計算每周給個model的最高價, 最低價跟平均價
  29. 29. III. Data Preprocessing 29 Make features {library: magrittr, dplyr, lubridate} » (1) 定義時間相關欄位 Date -> Week; Month ; Quarter [下列範例] Date -> Week; Week -> Month ; Month -> Quarter
  30. 30. III. Data Preprocessing 30 Make features {library: magrittr, dplyr} » (2) 計算每周給個model的最高價, 最低價跟平均價
  31. 31. III. Data Preprocessing Write data {library: xlsx} 31
  32. 32. Data Visualization 32
  33. 33. IV. Data Visualization » 匯入資料 [Get Data] » 定義資料集 [Edit Queries] » Visuals  Scatter plot  Scatter plot with animation  Box and Whisker Chart  Table  Filter 33
  34. 34. 匯入資料 [Get Data] 34 Report Data Relationships Pages
  35. 35. 匯入資料 [Get Data] 35
  36. 36. 定義資料集 [Edit Queries] 36
  37. 37. 定義資料集 [Edit Queries] 37
  38. 38. Visuals-Scatter plot 38
  39. 39. Visuals-Scatter plot with animation 39
  40. 40. Visuals-Box and Whisker Chart 40
  41. 41. Visuals-Filter 41
  42. 42. Visuals-Table 42
  43. 43. 43 Thank you~ Thank you!
  44. 44. References for Power BI 44
  45. 45. Start Using Power BI Desktop (1/2) Download Power BI Power BI Report Server » Link: https://www.microsoft.com/en- us/download/details.aspx?id=56723 » Plan to develop further Power BI Desktop » Link: https://www.microsoft.com/en- us/download/details.aspx?id=45331 » Personal use and share files with others » Update faster 45 Power BI Report Server
  46. 46. Start Using Power BI Desktop (2/2) A. Conduct Reports » 1. Choose visuals » 2. Prepare your data to fit the data structure of » visuals » 3. Create relationships for several tables » 4. Refer to official documents or on-line materials B. Practice » 1. Practice with samples (data pre-load) » 2. Generate other visuals » 3. Study how to add measures by DAX formula » 4. Refer to official documents or on-line materials 46
  47. 47. More Visuals 47 » Rich visuals are available in marketplace
  48. 48. References for Power BI 48 » Power BI website » https://powerbi.microsoft.com/zh-tw/desktop » Power BI Desktop 使用者入門指南 » https://docs.microsoft.com/zh-tw/power-bi/desktop-getting-started » Excel與Power BI https://www.zhihu.com/question/35324481 » Power BI 的零售分析範例教學 » https://docs.microsoft.com/zh-tw/power-bi/sample-retail-analysis » Power BI Visual Reference https://www.sqlbi.com/wp-content/uploads/videotrainings/dashboarddesign/visuals-reference- may2017-A3.pdf » Power BI Desktop 影片 https://docs.microsoft.com/zh-tw/power-bi/desktop-videos » Power BI Desktop 的 DAX 基本概念 https://docs.microsoft.com/zh-tw/power-bi/desktop-quickstart-learn-dax-basics

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