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團隊工作會議#1 簡報
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2014.1.16 於東吳大學 [校園海量資料分析人才培育工作坊] 的簡報分享。算是 Data Science Program (DSP) 從緣起、籌備、執行至今的階段性總結 (個人版)。謝謝一路上陪著走的朋友與同事們,讓我們一起擁有組織力。
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那些你知道的,但還沒看過的 Big Data 風景 ─ 致 Hadooper
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Fred Chiang
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Fred Chiang
Who really has the skills and talents to leverage the most value out of data? The Data Science Program (DSP) was co-founded by Code for Tomorrow and Etu. We believe that building and deploying a data science team consisting of members who possess and have the ability to utilize their different skill sets from a variety of industries is more practical and realistic. Versus hoping to find an individual data scientist who is an expert in a wide variety of technical fields ranging from math, statistics, and visualizations, as well as a solid background in other fields such as business, communication, and etc. The Data Science Program has identified four pertinent categories to place our members into. These four categories are Campaigner, Data Analyst, Data Hygienist, and Designer. Each team will have these four categories filled. During the training every team learns how to do data processing, data analysis, and visualization together with the sole purpose to use these skills to solve a common problem. After four weeks of intensive study, each team comes up with enterprise-grade team projects demonstrating the innovation of data-driven businesses. After two rounds of DSP Team Training, DSP has accumulated 10 team projects and has graduated more than 60 alumni who are passionate about data science. During this journey of developing and deploying teams trained in data science, the most valuable aspects we walked away with was the witnessing of members growing in confidence from the learning and experience, the building of team work, and the overall growth of each individual. At the end of the day, our hope of as members of DSP, including myself is to instill and motivate more people to devote themselves to the exploration of data science. Now think about how you can do the same.
Summary of Insights Learned from the Data Science Program Team Training
Summary of Insights Learned from the Data Science Program Team Training
Fred Chiang
2014.1.16 於東吳大學 [校園海量資料分析人才培育工作坊] 的簡報分享。算是 Data Science Program (DSP) 從緣起、籌備、執行至今的階段性總結 (個人版)。謝謝一路上陪著走的朋友與同事們,讓我們一起擁有組織力。
資料科學團隊人才培育分享 ─ 以 DSP 為例
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Fred Chiang
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資料的大量增長已經是事實,如何能夠提取資料的價值,也成了社會、商業、政府共同的利益課題。綜觀資料價值的提取,資料科學的能量,在不同的領域,均扮演關鍵的價值轉兌力量。 吾人已知資料科學是跨界的,與其寄希望於難覓的資料科學家一人,不如更關注於如何培養一個專業分工的資料科學團隊。本計畫的宗旨,即在希望透過對生活資料的收集、處理、分析、視覺化呈現、故事形塑、擬定行動的過程,分門規劃,引發社會各界對資料科學的興趣,從中培養對應人才,最終回饋於社會。
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This slides desk had been present in the Big Data Taiwan Forum 2013 which was hosted by Wired Taiwan on April 26.
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總結阻礙企業導入 Big Data 解決方案的因素,除了大環境的景氣因素,其餘幾乎可歸結為對「價值」與「技術」的不確定與不熟悉。此場將帶領大家預覽 Big Data Taiwan 2013 整天的內容精華,具體說明 Big Data 的「價值」洞見與展現,「技術」養成與發展,配合戰略探討與驅動,以降低企業的不確定感,協助數據價值策略的發展。
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This is my keynote slides for Etu Solution Day 2012 which was held on Dec, 20, 2012 @Taipei, Taiwan. I had summarized the market status of Big Data in Taiwan and predicted the trend in 2013.
ESD 2012 Keynote: What Is the next Big Data?
ESD 2012 Keynote: What Is the next Big Data?
Fred Chiang
Etu Appliance Presented Technology Innovation Awards by TAITRONICS
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Etu Appliance - 2012 TAITRONICS Technology Innovation Awards
Fred Chiang
2012.05.24 於 「Big Data Taiwan 2012」的 Keynote 講稿。 主講者:Etu 副總經理/ 蔣居裕 《議題簡介》 無論是企業區域網路,還是開放的網際網路,在巨大的結構化與非結構化資料的背後,其實充滿著各種行為意圖,以及人、事、物、時、地的多維度關聯。商業的日益競爭,已經來到了一個除了講求行銷創意,還要擁有巨量資料處理與分析技術,才能出奇制勝的時代。有人形容 Big Data 的價值挖掘,就像是在攪拌混凝土,若在尚未完成前就中斷,將導致前功盡棄,全無可用的窘境。對 Big Data 的意圖與關聯探索,必須是 End-to-End 全程的照料,方得實現。本議程將舉例說明這個有序到永續的過程,讓聽者更能領略意圖與關聯充滿的世界。
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Big Data 101 一 一個充滿意圖與關聯世界的具體實現
Fred Chiang
於 2012.4.18 精誠資訊「行雲流水」系列活動之二「雲」的 Keynote 講稿。說明經營雲端運算的兩條產業鏈,需要不同的核心能力。並指出雲端服務其實本質還是網路服務,台灣歷經 Web 1.0 與 2.0,都還有一時或存活下來的英雄,但雲端時代,台灣幾乎找不到雲端服務的 local hero,這是為什麼?值得大家深思。
破雲而出 — 重新發現您的雲端策略
破雲而出 — 重新發現您的雲端策略
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所知有雲 Team meetup 2
所知有雲 Team meetup 2
Fred Chiang
「所知有雲」 - 它是一場編輯行動 - 它以維基百科 (Wikipedia) 為載體 - 它的目標是要為雲端運算留下可持續維護的中文知識 - 它由你、你、你、你、我共同發起
「所知有雲」:維基百科雲端運算中文條目編輯行動發起說明
「所知有雲」:維基百科雲端運算中文條目編輯行動發起說明
Fred Chiang
Introduction of Elaster Labs, the 1st PaaS in Taiwan, developed and operated by TCloud Computing.
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Elaster Labs, the 1st PaaS in Taiwan
Fred Chiang
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Action Intelligence for Social Good
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Big Data vs. Open Data
那些你知道的,但還沒看過的 Big Data 風景 ─ 致 Hadooper
那些你知道的,但還沒看過的 Big Data 風景 ─ 致 Hadooper
Big Data 現象,以及現象中的我們
Big Data 現象,以及現象中的我們
Summary of Insights Learned from the Data Science Program Team Training
Summary of Insights Learned from the Data Science Program Team Training
資料科學團隊人才培育分享 ─ 以 DSP 為例
資料科學團隊人才培育分享 ─ 以 DSP 為例
資料價值 — 一位資料產品經理的視野
資料價值 — 一位資料產品經理的視野
台灣生活資料科學團隊養成計畫 (@Data Weekend #5)
台灣生活資料科學團隊養成計畫 (@Data Weekend #5)
轉兌數據的價值 — 從導購到策購
轉兌數據的價值 — 從導購到策購
Big Data 102 - Crossovers 成長之旅導覽 (Keynote for Big Data Taiwan 2013)
Big Data 102 - Crossovers 成長之旅導覽 (Keynote for Big Data Taiwan 2013)
ESD 2012 Keynote: What Is the next Big Data?
ESD 2012 Keynote: What Is the next Big Data?
Etu Appliance - 2012 TAITRONICS Technology Innovation Awards
Etu Appliance - 2012 TAITRONICS Technology Innovation Awards
Big Data 101 一 一個充滿意圖與關聯世界的具體實現
Big Data 101 一 一個充滿意圖與關聯世界的具體實現
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破雲而出 — 重新發現您的雲端策略
所知有雲 Team meetup 2
所知有雲 Team meetup 2
「所知有雲」:維基百科雲端運算中文條目編輯行動發起說明
「所知有雲」:維基百科雲端運算中文條目編輯行動發起說明
Elaster Labs, the 1st PaaS in Taiwan
Elaster Labs, the 1st PaaS in Taiwan
所知有雲 Team meetup 1
1.
所知有雲 team meetup-1 ●
各成員自我介紹 (everyone) ● 目前籌備狀況報告 (Fred) ● 討論事項 (Fred) ● 臨時動議 (everyone can issue) ● 結論: Action Item 2011.05.18 ˙19:00-22:00 @ Mr.Brown 北科大店
2.
各成員自我介紹 (everyone)
3.
目前籌備狀況報告 (Fred) ● Domain Cloud101.tw go live ●
Web site goes live with AWS EC2 (micro instance) ● Google Apps is on ● team@cloud101.tw ● fredchiang@cloud101.tw ● MediaWiki installed ● Pages: 條目總覽、中英詞彙對照表 added
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Team
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討論事項 (Fred) ● 哲學:快樂
/ 群體 / 品質 ● Working flow ● Ebook (for iOS/Androidbased Tablet) publishing system by MediaWiki
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臨時動議 (everyone can
issue)
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結論: Action Item
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