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。
在接連勇奪三個產品創新獎項之後,亞洲 Big Data 解決方案領導品牌 Etu 今天舉辦「Etu Solution Day 2012」,與合作夥伴聯手展出了一系列以其核心產品 Etu Appliance 發展出來的 Big Data End-to End 解決方案,並在會中提出 2013 年台灣 Big Data 市場的趨勢預測。Etu 認為,隨著不同行業的 Big Data 首批應用一一成形落地,企業擁抱 Big Data 的力道將在新的一年有明顯加重的趨勢。
首屆的「Etu Solution Day」特別針對電子商務、零售、電信、金融、高科技製造、政府及交通運輸行業,一次匯集具有 Hadoop 經驗的 Big Data 應用軟體開發商,以及可接取 Hadoop 平台的工具廠商,與焦點行業來賓分享經驗成果。Etu 在會中發表對 2013 年台灣 Big Data 市場的五大前瞻性預測,包括:一、本地不同行業的 Big Data 應用案例將一一浮現;二、”Medium” Data 出現在更多企業 Big Data 應用場景;三、Hadoop 相關專業教育訓練課程漸熱;四、從 Quantified Self、Enterprise Data、Open Data、到 Internet-scale Data,資料分析蔚為顯學; 五、Open Data 方興未艾,各級政府、不同部門的開放策略與腳步不一,來自民間的挑戰也不斷。
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Trinity 大幅提昇企業面對大量快速變化資訊潮流時的競爭力。
現今企業 BI 多建於 RDBMS 上,伴隨大量的 ETL 與資料交換作業。在導入 Hadoop Big Data 應用之後, 如何有效地與既有 BI 系統介接,且進一步整合,以發揮整體綜效,將是一項挑戰。
Trinity 藉由優越的架構,在傳統 Structured Data 與 Hadoop Big Data 的應用間,建立無縫的交換作業,讓資訊分析人員直接運用熟悉的方式,以大幅降低導入 Big Data 應用時的學習曲線與後續對系統維運所投入的人力。
在接連勇奪三個產品創新獎項之後,亞洲 Big Data 解決方案領導品牌 Etu 今天舉辦「Etu Solution Day 2012」,與合作夥伴聯手展出了一系列以其核心產品 Etu Appliance 發展出來的 Big Data End-to End 解決方案,並在會中提出 2013 年台灣 Big Data 市場的趨勢預測。Etu 認為,隨著不同行業的 Big Data 首批應用一一成形落地,企業擁抱 Big Data 的力道將在新的一年有明顯加重的趨勢。
首屆的「Etu Solution Day」特別針對電子商務、零售、電信、金融、高科技製造、政府及交通運輸行業,一次匯集具有 Hadoop 經驗的 Big Data 應用軟體開發商,以及可接取 Hadoop 平台的工具廠商,與焦點行業來賓分享經驗成果。Etu 在會中發表對 2013 年台灣 Big Data 市場的五大前瞻性預測,包括:一、本地不同行業的 Big Data 應用案例將一一浮現;二、”Medium” Data 出現在更多企業 Big Data 應用場景;三、Hadoop 相關專業教育訓練課程漸熱;四、從 Quantified Self、Enterprise Data、Open Data、到 Internet-scale Data,資料分析蔚為顯學; 五、Open Data 方興未艾,各級政府、不同部門的開放策略與腳步不一,來自民間的挑戰也不斷。
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Trinity 大幅提昇企業面對大量快速變化資訊潮流時的競爭力。
現今企業 BI 多建於 RDBMS 上,伴隨大量的 ETL 與資料交換作業。在導入 Hadoop Big Data 應用之後, 如何有效地與既有 BI 系統介接,且進一步整合,以發揮整體綜效,將是一項挑戰。
Trinity 藉由優越的架構,在傳統 Structured Data 與 Hadoop Big Data 的應用間,建立無縫的交換作業,讓資訊分析人員直接運用熟悉的方式,以大幅降低導入 Big Data 應用時的學習曲線與後續對系統維運所投入的人力。
Can data virtualization uphold performance with complex queries? (Chinese)Denodo
Watch full webinar here: https://bit.ly/3fQFUEY
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Register this webinar as we explore the basis of the 'performance' myth and examine whether there is any underlying truth to it.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Can data virtualization uphold performance with complex queries? (Chinese)Denodo
Watch full webinar here: https://bit.ly/3fQFUEY
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Register this webinar as we explore the basis of the 'performance' myth and examine whether there is any underlying truth to it.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Bringing Email Development from 1996 to 2016
Free yourself from a sea of nested <tables>’s, <tr>’s, and <td>’s, and into modern web development practices. We’ll show you how to circumvent the treacherous table-based email layout with the power of the sparkling clean templating language of the open source Foundation for Emails 2 — taking your code from 160 lines of deeply nested, ugly code to 40 clean and simple ones.
What you’ll learn:
Coding an email in Foundation for Emails 2.
The power of Sass in email development
Templating languages like Panini
How will this information improve the email creation process or improve the subscriber experience? Teaching a cutting-edge email framework that keeps code reusable and clean and developers happy and empowered. We’ll showcase how to make the best of the web development world work for html email.
Method for Controlling Buckthorn - Society for Ecological Restoration 2011John Lampe
This presentation describes a novel way to control woody invasive plant species like buckthorn. It is especially suitable for small woodland owners and managers.
presented at CLSA's 2015 Japan Forum this presentation discusses how mobile phones have become a integral part of the shopping experience for people of all ages. the notion of the "fifth sense" was introduced by McCann's Truth about Youth research in 2011to explain how people have adopted their smart phone as an integral part of how they sense the world. in fact it has become an important sensory addition for many aspects of life.
ESD 2012 Keynote: What Is the next Big Data?Fred Chiang
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.
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。
Modernising Data Architecture for Data Driven Insights (Chinese)Denodo
Watch full webinar here: https://bit.ly/3phVEEv
In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics, it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But, that scenario is rapidly changing with the increasing adoption of real-time data virtualization - A paradigm shift in the approach that organisations take towards accessing, integrating, and provisioning data required to meet business goals.
As data analytics and data-driven intelligence takes center stage in today’s digital economy, logical data integration across the widest variety of data sources, with proper security and governance structure in place has become mission critical.
Register this webinar to learn:
- How you can meet the challenges of delivering data insights with data virtualization
- Why Data Virtualization is increasingly find enterprise-wide adoption
- How customers are reducing costs and delivering faster insight
Similar to Big Data 102 - Crossovers 成長之旅導覽 (Keynote for Big Data Taiwan 2013) (20)
Opening Keynote for HadoopCon 2014
我們的身邊、網路上,圍繞著太多的 Big Data 論述與技術,Hadooper 今天聚集在這裡,都已經是 Big Data 的相關利益者,然而, 今天我們所理解的 Big Data,大部分都是透過自身的體驗而來,但 Hadoop Ecosystem 太過龐雜,Use Case 不同,必須取不同的 OSS 專案來完成,如此想來,我們哪一個人何曾看過所有的 Big Data 風景呢?
此 Talk 告訴我們如何透過更多的風景之窗,將 Big Data 的不同天地,看得更多更透。
Summary of Insights Learned from the Data Science Program Team TrainingFred 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.
17. Open Government Data — 來自學界的聲音
2013.01
中央研究院
資訊科技創新研究中心 台灣創用CC計畫 出版
《藏智於民:開放政府資料的原則與現況》
http://creativecommons.tw/downloads/handbook_open_g
ov_data_2012.pdf
17
19. Open Data — 來自民間的聲音
Code for Tomorrow:寫程式,改造社會
2013.02.24
International Open Data Day 2013, Taipei
首度在台北舉行,全世界有超過 100 個城市響
應,在亞洲地區, 今年有日本、台灣、韓國、
泰國、馬來西亞與香港等地加入。參加者包含需
求方、開發者、數據家、設計師、媒體人、以及
社會公民等,超過 130 人。
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22. Open Corporate Data
Facebook
EZprice Open Graph 人際社群的關聯
Open Data 消費者行為、
電子商務、價格監控
《TW Hadoop 相關社群關聯圖》, sourced by Jazz Wang, 2013.3.22
22
23. Open NGO/NPO Data
The World Bank – Open Data / DataBank
Google Public Data Explorer
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24. Open Data – Big Data - Cloud
案例:1000 Genomes Project http://en.wikipedia.org/wiki/1000_Genomes_Project
資料量:100TB (1,700+ DNA sequenced)
資料儲存:AWS S3
資料費用:free
運算費用:computing resources for analyzing
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32. Etu Appliance,創新得獎高手 B1-3
2012 TAITRONICS 101 年資訊月 China Big Data 2012 2012 年度雲計算
2012 雲端創新獎
科技創新優選獎 傑出資訊應用暨產品獎 年度大數據創新企業 Hadoop 創新產品獎
不可能更容易的 Hadoop 企業平台
32
33. 結論:2013 台灣 Big Data 市場五大預測
1. 本地不同行業的 Big Data 應用案例將一一浮現;
2. ”Medium” Data 出現在更多企業 Big Data 應用場景;
3. Hadoop 相關專業教育訓練課程漸熱;
4. 從 Quantified Self、Enterprise Data、Open Data、到
Internet-scale Data,資料分析蔚為顯學;
5. Open Data 方興未艾,各級政府、不同部門的開放策略與腳步
不一,來自民間的挑戰也不斷。
~ Etu 2012.12.20
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34. 祝 各位 Big Data 旅途愉快
本日收穫滿滿
我們 Big Data Taiwan 2014 再見
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