CML's Talk Slides at Johnson Health Tech, 2020

3. 東海大學為因應智慧科技所帶來的破壞性創新，為了協助台灣產業
進行創新轉型與產業升級，在藍濤亞洲以及亞馬遜AWS協力夥伴
之鼎力協助下，成立東海大學智慧轉型中心，簡稱 TISC。
（Tunghai Industry Smart-Transformation Center）
中心簡介
主要業務
協助產業進行 數位轉型 與 創新升級 。
輔導產業建構 智慧創新 與 數位轉型 智能系統。
(產)(官)(學)(研)的產學合作及知識交流。
創新轉型
產業升級
資源整合

4. 主要成員
東海大學管理學院
陳鴻基 院長
(智慧轉型中心 主任)
藍濤亞洲
黃齊元 總裁
(智慧轉型中心 執行長)
東海大學智慧轉型中心
林鴻志 副營運長
創新轉型 產業升級 產學合作

5. Big Data 大數據分析
Johnson 喬山
資訊工程系 & 雲端創新學院
賴俊鳴 助理教授

6.  Linkedin
 大學 (2011)
 Ph.D (2019)
 Assistant Prof.
（2019.08）
2021/10/18 6
Bio

7. 2021/10/18 7

8.  AWS Certified Instructor
 AWS SAA & CLF Certificate
 研究興趣：社群網路數據分析、應用大數據、
人機互動
 WSET Level I & II
 旅遊點數玩家
2021/10/18 8
關於我
Chun-Ming Lai
AWS Certified Solutions Architect - Associate
Nov 03, 2019
Nov 03, 2022
Validation Number WM1ENMBCGEE1QY51
Validate at: http://aws.amazon.com/verification
Chun-Ming Lai
Sep 21, 2019
Sep 21, 2022
Validation Number MGFL2VQCGE1E1PC5
Validate at: http://aws.amazon.com/verification

9. 2021/10/18 9

10.  數據很多，多少什麼規模？
 多樣化的資料
 資料即時性
 (深 廣 快)
2021/10/18 10
什麼是大數據！？

11. 2021/10/18 11

12. 2021/10/18 12
大數據神話

13.  數據分析發現啤酒與尿布間在銷售上有高度相關性
 理解到前述發現的真正原因
 運用這樣發現將兩類產品放在一起賣，從而提升銷
售業績 !?
 發覺過往沒意識到客群與客群生活型態、有意義的
價值創造 （新手家長俱樂部etc.）
2021/10/18 13
事實or神話？

14.  2012~2015 大數據、雲端計算、AI、VR/AR、
區塊鏈、物聯網
 儲存、網路漸趨成熟
 價值供應鏈需求滿足價值網絡(食、衣、住、
行、育、樂)
2021/10/18 14

15.  有興趣開車旅遊汽車需求與里程數高輪胎
需求
 自媒體帶動地圖、餐飲、住宿
 營業用車隊 (維修、更新、庫存、調校)
2021/10/18 15
米其林

16.  PPK (pay per kilometer) 輪胎解決方案
 MyBestRoute 車輛路線規劃
 MyTraining 數位化新駕駛訓練
 MyRoadChallenge 良好駕車習慣
 MyInspection 數位化車輛檢查服務
2021/10/18 16
Effitires 輪胎管理系統

17.  節能需求、燃料節省目的
 若無達到節能目的，支付賠償
 輪胎經銷商 問題解決夥伴 (引進第三方數據
合作夥伴)
2021/10/18 17
Effifuel (2014)

18. 2021/10/18 18

19. Google Facebook Twitter NSA Ebay Spotify
100 PB 600 TB 100 TB 29 PB 100 PB 2.2 TB
2021/10/18 19
每天處理資料數量
https://followthedata.wordpress.com/2014/06/24/data-size-estimates/

20. Volume
Data
Quantity
Velocity
Data Speed
Variety
Data Types
2021/10/18 20
Big Data 3Vs
IoT、5G、Infra
GeoSpatial Data
Audio & Video

21. 白血球數量
Intelligence

22. Visualization (視覺化)
Analysis (分析)
Processing (處理)
Storage (儲存)
Collection (收集)
2021/10/18 22
Big Data 5 Steps
Privacy
(隱私)
Security
(安全)

23. 2021/10/18 23
Collection
Source:城田真琴(2013)

24. 2021/10/18 24
Collection
Source:城田真琴(2013)

25.  內部整理、市場調查
 顧問業
 偷拐搶騙
 社群媒體
2021/10/18 25
資料來源

26. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
營收 2018Q4
Branch 營收 利潤 占比
AWS 7.4 B 2.17 B 57%
北美市場 44.1 B 2.25 B 59%
國際市場 20.8 B (0.64 B) (16%)

27. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises

28. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Flexible capacity
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Fixed capacity
 Procurement and setup
 Limited geographic regions
 Install and configure
 Physical space, cooling, power
 Cabling, networking, racks, servers,
storage
 Labor, certification…
 Click to order resources
 Immediate access
 Go!

29. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Flexible capacity
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Fixed capacity
 Procurement and setup
 Limited geographic regions
 Continually lower prices
 Optimize costs with pricing options
 Patches and upgrades
 Labor and system administration

30. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Flexible capacity
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Fixed capacity
 Procurement and setup
 Limited geographic regions
 Application development  Non-differentiated operations

31. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Flexible capacity
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Fixed capacity
 Procurement and setup
 Limited geographic regions
 Provision the resources you need
 Turn off what you don’t need
 Idle resources
 Inadequate capacity

32. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Flexible capacity
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Fixed capacity
 Procurement and setup
 Limited geographic regions

33. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Procurement and setup
 Limited geographic regions
 Flexible capacity  Fixed capacity
 Fast, on-demand provisioning  Lengthy, labor-intensive provisioning

34. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Procurement and setup
 Limited geographic regions
 Flexible capacity  Fixed capacity
 Deploy in any AWS region on-demand
 Lower latency to distributed user
bases
 Costly to build a global
infrastructure

35. © 2017 Amazon Web Services, Inc. or its affiliates. All rights reserved.
CCA 1.01: What is Cloud Computing ► Part 2: Comparing Cloud to On-prem
Cloud vs. On-Premises Comparison
Cloud On-Premises
 No upfront investment
 Low on-going costs
 Focus on innovation
 Speed and agility
 Global reach on demand
 Large initial purchases
 Labor, patches and upgrade cycles
 Systems administration
 Procurement and setup
 Limited geographic regions
 Flexible capacity  Fixed capacity

36. 
2021/10/18 36
Storage 媒介

37. 2021/10/18 37

38.  Backup (備份、異地)
 DR (災難復原)
 Versioning (版本控制)
 MFA Delete (防止刪除)
 Identity Control (身份控管)
2021/10/18 38
Storage (以Amazon S3 為例)

39.  SQL 寫得好，要飯要到老。

2021/10/18 39
Relational vs NoSQL

40.  Extract Transform Load (ETL)
 分析目標與方針
 清理資料、資料轉換、Data Pipeline
 資料科學家(DS)與資料工程師(DE)的協奏曲
 人工智慧與機器學習
2021/10/18 40
Processing and Analytics

41.  瑕疵檢測 (智慧製造)
 牛發情與否 (智慧農業)
 術後敗血症 (智慧醫療)
 攝護腺功能 (智慧馬桶醫療)
2021/10/18 41
應用領域

42. Data Information Knowledge Wisdom

43. 
2021/10/18 43
Visualization

44. Facebook 允許朋友數
100003468896671 高婷婷 45xx
100004123536871 賴婷婷 45xx
100003251795795 陳婷婷 4xxx
使用數學方法偵測可疑帳號
5000

45. Privacy
• 臉部辨識及社會安全系統
• “We collect as much as we want, then we will
figure out…”
Transparency and Collaborative Computing
• GDPR, Intellectual Property protection
Adversarial Machine Learning
• Integrity and Validity of the Sensor Inputs
12/06/2019
User/sensor Data Edge device/sensor Cloud
AI-based Algorithms

46. Confidentiality, protection, policy and law
誰擁有這些資料？Edge、雲端、資料中心?
Understanding what information about
“me” has been collected and how it is/will
be used
• GDPR (General Data Protection Regulation)
12/06/2019