Data Thinking Workshop 03
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This document discusses how businesses can incorporate data science concepts into their processes. It covers common data science applications in e-commerce like sales trend analysis, order analysis, customer segmentation, search optimization, and recommendation systems. It also discusses how businesses can develop data products like customized services, process optimization, and automated services using techniques like chatbots, image recognition, and natural language processing. Finally, it discusses the roles of data teams in businesses and common analytical skills and tools used in data science.
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Data Thinking Workshop 03
- 2. 劉佳欣 (Rafe C. H. Liu) 交通大學運輸與物流管理學系博士 ○ 消費者行為、航空營收管理 ○ 、 、 Manager, Data Science and Analytics 2 DATADATA DATA 旅遊電商 資料科學 R
- 5. Types of Analytics Capability 5Source: Gartner Says Advanced Analytics Is a Top Business Priority (October 2014) 描述型分析 診斷型分析 預測型分析 指示(處方)型分析 what why what likely how COST RISKS
- 6. Data Products 6 Research & Development Business Managerial Level Operational Level Reporting BI Customized Analytics QA, QC Monitoring and Control Data Models and Algorithms
- 8. 電子商務資料科學應用場景 (Application Scenario) 資料管理平台 ○ 顧客買了什麼？ 銷售趨勢掌握 ○ 什麼賣的最好？ 訂單分析 ○ 哪些顧客在買？ 客群分析 (RFM Clustering) ○ 怎麼讓顧客買得更順利，更快找到商品？ 搜尋優化 (Search Ranking) ○ 如何讓顧客買更多？個性化銷售？ 推薦系統 (Recommender) ○ …. 資料產品 ○ 個性化服務 (CRM) ○ 流程優化 (Optimization) ○ 服務升級 (Automation) • ChatBot (NLP): HipMonk • 攜程小詩機 (Image Recognition, Text Mining + NLP) 8
- 9. 9https://blog.dataiku.com/machine-learning-explained-algorithms-are-your-friend 趨勢、相關、預測 彈性分析 (log, double-log) 客戶留存率 (Churn Rate) 存活分析 客戶購買因素 點擊分析 離散、連續型的分類預測 多棵決策樹 顧客分群 (RFM) 推薦系統 改良隨機森林學習演算法 Kaggle 比賽勝率最高 圍棋 影像識別 自然語言處理 金融相關 APPLICATIONS (包括但不限於)
- 10. 欺生 殺熟 10
- 12. 12 “A Good Picture is worth a thousand words”
- 14. Select / Read the chart • Purpose, Target audience • Data: Types, Dimensionality • Messages - chart types – Composition / Distribution – Relationship / Comparison – Time • Combo / Special charts • Describe charts – Units! – size, position, changes, outliers – shifts, trends, areas – color groups, patterns 14
- 16. 16 A B C D C A B D 表格 TABLE 長條圖 BAR CHARTS
- 17. 17 交叉表 CROSS TABLE A B C D X1 X2 X3 C B D A X2 X3 X1 堆疊圖 STACKED CHART
- 18. 18 柏拉圖 PARETO CHART A B C D %unit
- 22. What You Sell 22https://blog.omniconvert.com/ecommerce-customer-retention-rate-optimization.html/
- 23. 23 Qty 銷售數量 Price 商品平均單價 Qty 銷售數量 Gross Profit 商品平均毛利 Qty 銷售數量 Margin 單一商品毛利率 Qty 銷售數量 Margin 單一商品毛利率 Qty 銷售數量 Margin 單一商品毛利率 Price 商品平均單價 Gross Profit 商品平均毛利 Qty 銷售數量 Income 收入 period cty. prod_no Qty Income 2018.5 JP HFZ00000000 5 15,000 2018.5 JP HFZ00000021 8 25,600 period cty. prod_no Qty Income Price (avg.) Cost (avg.) 2018.5 JP HFZ00000000 5 15,000 3,000 2,500 2018.5 JP HFZ00000021 8 25,600 3,200 3,000 period cty. prod_no Qty Income Price (avg.) Cost (avg.) Gross Profit (avg.) margin 2018.5 JP HFZ00000000 5 15,000 3,000 2,500 150 5% 2018.5 JP HFZ00000021 8 25,600 3,200 3,000 200 6.25% period cty. prod_no Qty Income Price (avg.) Cost (avg.) Gross Profit (avg.) margin 2018.5 JP HFZ00000000 5 15,000 3,000 2,500 150 5% 2018.5 JP HFZ00000021 8 25,600 3,200 3,000 200 6.25% 2018.5 KR HFZ00000168 3 6,000 2,000 1,800 200 10%
- 25. 資料團隊 25 TimTeam
- 26. Data Teams Linkedin ○ Decision Sciences Team, which analyzed key product metrics and explored usage data. ○ Product Data Science team, is an amazing group of data scientists who came up with innovative new data-powered features that give off new data for analysis. 26 Booking.com LinkedIn had one of the first data science teams. Now it’s breaking up the band (2014) Analytics & Research Product Management
- 27. Team Roles 27 Business Analyst Domain Expert Qualitative (Planning) Business Insights Strategy Excel, R … Data Scientist Analytical skills Scientific (Exploration) Data Analysis Modeling R, Python … Data Engineer Computer Science Engineering (Development) Technical skills Implementation Python, Java, Scala … include but not limited to
- 28. Data Team 28 TEAM ROLES ANALYTICAL STACKS METHOD -OLOGY TASKS skills tools arch. Managerial Science Engineering PCs, Self-hosting Server Google, AWS, Microsoft Excel R, Python Java, Scala Business Analyst Data Scientist Data Engineer Data Acquirement Data Management Analytics Reporting Deployment Multivariate Analysis Machine Learning Data Mining Deep Learning, AI
- 30. Data Scientists Skill Sets 30
- 31. Clustering Data Scientists 31 250 self-reporting web survey Source: H.D. Harris et al. (2013), Analyzing the Analyzers Data Business Person Data Creative Data Developer Data Researcher Business ML/BigData Math/OR Programming Statistics Skills Groups “I think of myself as a/an X” Data Business Person Leader Business Person Entrepreneur Data Creative Jack of All Trades Artist Hacker Data Developer Developer Engineer Data Researcher Researcher Scientist Statistician
- 32. 32 Two interesting things happened in 1990s: • The number of new colors started to grow exponentially. • Pink/purple hues began to appear. It may have something to do with Lego’s business strategy and it’s said Lego wants to build stronger ties with girls’ market https://medium.com/@yanhann10/the-color-history-of-lego-bricks- 1e83ffea7b6d
- 34. Data Science 34 You can have data without information, but you cannot have information without data. https://research.facebook.com/
- 36. 36https://www.analyticsvidhya.com/blog/2015/07/difference-machine-learning-statistical-modeling/
- 39. 39 Bring Data to Life from theory to practice
- 44. 44吳文元 > 路上觀察學院 (201709) XX 油飯、米糕、湯圓， 是我吃過的，超美味的台中美食 ~林肯 (1809-1865)~ 不要因為配著林肯的照片， 就隨便相信林肯的話！ 您應該要自己 獨立思判， 親自去鑑定嘗試才對！ ~阿爾伯特，愛因斯坦~ 輝記 專業米糕、油飯、湯圓