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。
1. HadoopCon 2014
那些你知道的,但還沒看過的 Big Data 風景
─ 致 Hadooper
Etu 負責人 蔣居裕
@fredchiang
fredchiang@etusolution.com
September 13, 2014
2. 2
Who am I?
蔣居裕 Fred Chiang
Open xxx 的愛好者
資料價值的探索者
社群的參與者
Etu 負責人
) Blog —《Fred 豢養的雲中象》http://fredbigdata.blogspot.tw
all about Hadoop and Big Data
台灣少見以探討 Big Data 趨勢、技術、商業價值為主軸的專業部落格
15. 15
Data Science 的要素
人
分工
團隊
知識
技能
工具
資料
Domain
Pain
Point
Value
Up
16. How a typical software vendor approaches
16
Data Science
(generally a bunch of developers)
The Data Science Venn Diagram
1.
Developers think they
can handle the domain
properly, but actually
is not fully able to.
Approach
Listen to customers.
Result
Customers realize
the developer’s
capabilities are just
coding. They have
never dealt with the
danger zone.
http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
2.
Developers think they
can handle the
algorithm as easy as
an SQL command, but
actually is not able to.
Approach
Calls for help.
Result
Developers are just
coders. Machine
learning is a dream.
PRISM
稜鏡計畫
Technical Support Manager
24. 24
Etu is Hiring
1. Software Engineer, Hadoop Platform
2. Software Engineer, Etu Recommender / Etu Insight
3. Professional Service Engineer
4. Data Analysis / Data Mining Engineer
5. Technical Support Manager
Resume mail to : hr@etusolution.com