蛋塔賣你 (Data Mining)

這裡有30哈佛商業評論（HBR）上的大數據科學分析提供最新的技術和事件數據的世界的見解的文章。

Source : http://www.kdnuggets.com/2015/09/30-hbr-articles-analytics-big-data-science.html

On Data Science

1. Data Scientist: the sexiest job of the 21st century by Thomas H. Davenport and D.J. Patil (Oct 2012) 

How the idea of LinkedIn's People You May Know feature really clicked! The key player involved was a "Data Scientist", a title coined by the two authors.

1. The Sexiest Job of the 21st Century is Tedious, and that Needs to Change by Sean Kandel (Apr 2014) 

Which phase does a data scientist spend more time on? Data Discovery, data structuring and creating context. Should they shift their focus?

• What Every Manager Should Know About Machine Learning by Mike Yeomans (July 2015) 

With the right mix of technical skill & human judgment, machine learning could be a new tool for decision makers. Learn what mistakes to avoid.

• Data Scientists Don’t Scale by Stuart Frankel (May 2015)

We are at a new phase of big data. Is Data capture and storage now less relevant than making it more useful & impactful?

• Get the Right Data Scientists Asking the “Wrong” Questions by Josh Sullivan (Mar 2014) 

What makes an exceptional data scientist? Data by itself is meaningless. The skill & curiosity is what makes the difference.

• A Data Scientist’s Real Job: Storytelling by Jeff Bladt and Bob Filbin (Mar 2013) 

How to derive insights & intuitions from data? We “humanize” the data by turning raw numbers into a story about our performance.

• What Separates a Good Data Scientist from a Great One by Thomas C. Redman (Jan 2013) 

Better than the Best! Great data scientists bring four mutually reinforcing traits to bear that even the good ones can’t.

• Still the Sexiest Profession Alive by DJ Patil (Nov 2013) 

Data scientist jobs are very much in demand as companies grapple with the challenge of making valuable discoveries from Big Data. Is a huge crowd just joining the bandwagon?

1. 10 Kinds of Stories to Tell with Data by Tom Davenport (Nov 2013)
   Narrative is—along with visual analytics—an important way to communicate analytical results to non-analytical people. Explore the 10 types.
2. How to Start Thinking Like a Data Scientist by Thomas C. Redman (Nov 2013) 
   You don’t have to be a data scientist or a Bayesian statistician to tease useful insights from data. The author demonstrates how to think with a small exercise.
3. Stop Searching for That Elusive Data Scientist by Michael Schrage(Sep 2014) 
   Stop hunting for that data science unicorn and/or silver bullet. What to do instead?
4. How to Explore Cause and Effect Like a Data Scientist by Thomas C. Redman (Feb 2014) 
   While we can use data to understand correlation, the more fundamental understanding of cause and effect requires more.
5. 13. You May Not Need Big Data After All by Jeanne W. Ross, Cynthia M. Beath and Anne Quaadgras (Dec 2013) 
       Companies are investing like crazy in data scientists, data warehouses, and data analytics software. Should they channelize their efforts?
   14. Big Data Hype (and Reality) by Gregory Piatetsky-Shapiro (Oct 2012) 
       Does your big data have big impact? The potential of “big data” has been receiving tremendous attention lately. The author analyzes using practical scenarios.
   15. With Big Data Comes Big Responsibility by Harvard Business Review Staff (Nov 2014) 
       An interview with Alex “Sandy” Pentland, the Toshiba Professor of Media Arts and Sciences at MIT who talks about the principles " A New Deal on data".
   16. Inventory Management in the Age of Big Data by Morris A. Cohen (Jun 2015) 
       Managers will need to redesign their supply-chain processes to make effective use of new data to stay competitive.
   17. Why Health Care May Finally Be Ready for Big Data by Nilay D. Shah and Jyotishman Pathak (Dec 2014) 
       Explore the key elements that are crucial for health care to truly capture the value of big data.
   18. What the Companies Winning at Big Data Do Differently by Satya Ramaswamy(Jun 2013) 
       A brief analysis of Netflix success using consumer behavior data. How big data can change the structure of an industry by fundamentally shifting the power.
   19. Stop Worrying About Whether Machines Are “Intelligent”. by JC Spender (Aug 2015) 
       Are we right to be afraid that the machines may take over? An interesting read about Turing's test and machine intelligence.
   20. Are You Data Driven? Take a Hard Look in the Mirror. by Andrew McAfee and Erik Brynjolfsson (Oct 2012) 
       The term “data driven” is penetrating the lexicon ever more deeply these days. What are the traits?
   21. Marketers Flunk the Big Data Test by Mick Collins (Apr 2015) 
       Marketing in particular is feeling the pressure to embrace new data-driven customer intelligence capabilities. Learn more about the key findings.
   22. 22. Simplify Your Analytics Strategy by Narendra Mulani 
           Companies can get stuck trying to analyze all that’s possible and all that they could do through analytics. How to strategize to avoid this?
       23. Making Advanced Analytics Work for You by Dominic Barton and David Court 
           Big data could transform the way companies do business, delivering performance gains. How to get the strategy suited to your needs?
       24. A Predictive Analytics Primer by Tom Davenport (Sep 2014) 
           A brief read on predictive analytics with a focus on customers.
       25. The Persuasiveness of a Chart Depends on the Reader, Not Just the Chart by Scott Berinato (May 2015) 
           What's more a better way to persuade people than visual information? An interesting read on how good is your data chart is based on the audience's understanding of it and cognitive state.
       26. Analytics 3.0 by Thomas H. Davenport (Dec 2013) 
           A new resolve to apply powerful data-gathering and analysis methods not just to a company’s operations but also to its offerings—to embed data smartness into the products and services customers buy.
       27. What People Analytics Can’t Capture by Daniel Goleman (July 2015) 
           The latest fad in human resources, using big data analytics and personality test scores to predict who is best for a given job – so-called “XQ.”. Do the scores capture accurately all the required skills?
       28. Gamification Can Help People Actually Use Analytics Toolsby Lori Sherer-(Feb 2015) 
           You have to identify the right data and develop useful tools, such as predictive algorithms. But then comes an even tougher task: getting people to actually use the new tools.
       29. What Popular Baby Names Teach Us About Data Analytics by Kaiser Fung (Apr 2015) 
           Find out what FiveThirtyEight’s Nate Silver and Allison McCann did with the baby names dataset sets an example for all data analysts. Their article represents the best of data journalism.
       30. A Better Way to Tackle All That Data by Chris Taylor (Aug 2013)
           Hampered by a shortage of qualified data scientists to perform the work of analysis, big data’s rise is outstripping our ability to perform analysis and reach conclusions fast enough.