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Weekly Digest - May 26

The full version is always published Monday. Starred articles are new additions, posted between Thursday and Sunday

Featured Contributions


Added by Vincent Granville on May 21, 2014 at 9:30am — No Comments

50 big data companies to follow

Posted on Sandhill.…


Added by Mirko Krivanek on May 20, 2014 at 4:30pm — 2 Comments

Research Brief: Four Functional Clusters of Analytics Professionals

Authored by:

Pasha Roberts, Chief Scientist

Greta Roberts, CEO

July 2013

Key Findings

Digging into a cross-industry study of analytics professionals, we identify four distinct patterns of how these workers spend their week: (1)…


Added by Mike Kennedy on May 20, 2014 at 10:00am — 6 Comments

Data Warehouse Architecture

According to Weisensee et al., Data warehouse architecture follows following principles:

  • Data Sources
  • Data Warehouses
  • Data Marts
  • Publication Services

Extraction, Transformation and Loading (ETL):

ETL process is the foundation of BI. Success and failure of BI projects depends upon ETL process. It plays a vital role to integrate and enhance the worth of data. After the extraction, cleansing and arrangement…


Added by Avesh Dhakal on May 20, 2014 at 12:30am — No Comments

Automatic Identification of Replicated Criminal Websites Using Combined Clustering Methods

The following publication was presented at the 2014 IEEE International Workshop on Cyber Crime and received the Best Paper Award on 5/18/2014.  The original IEEE LaTeX formatted PDF publication can also be downloaded from here: IWCC Combined Clustering.…


Added by Jake Drew Ph.D. on May 19, 2014 at 6:30pm — No Comments

Proposal for a new type of scoring system

In digital analytics, scoring Internet traffic is used to detect click fraud, and to find types of search keywords that convert well (to a sale). Quite often (for large ad networks) conversion data is poor or challenging: some clicks have a 0.2% conversion rate, some have a 30% - depending on the type of website, price, product, conversion type and other factors (even hour of the day has an impact).…


Added by Mirko Krivanek on May 18, 2014 at 6:30pm — No Comments

Starting down the path of Data Science

I've always been interested in data, how it's interpretted and the different ways it can be sliced. However, I've always considered statstics itself to be a math that I didn't like. As "data science" and "big data" became more popular, however, I started to look into ways to learn more about it and possibly use it as a entry into another act of my career.

The advent of MOOCs has opened up the possibility of learning new subjects and subject-focused websites like Data Science Central…


Added by Don VanDemark on May 18, 2014 at 1:00pm — 2 Comments

My data science journey

I describe here the projects that I worked on, as well as career progress, starting 25 years ago as a PhD student in statistics, until today, and the transformation from statistician to data scientist that occurred slowly and started more than 20 years ago. This also illustrates many applications of data science, most are still active.

Early years

My interest…


Added by Vincent Granville on May 17, 2014 at 12:00pm — 1 Comment

R as Ad Hoc

I was reading through my Twitter feed the other day and saw a comment about the R language being too ad hoc for users.  It got me thinking, "Is that bad? Aren't most languages initially seen as ad hoc?".  

The beauty of R as a data science tool is its "ad hocedness" in that its use can satisfy multiple interests.  Initially I can see this as troublesome in that learning the specificity of a tool's use can be daunting.  But in the long-run I think this benefits a…


Added by Justin on May 15, 2014 at 5:04pm — No Comments

Biggest Potential for Big Data: The Expanding Universe of Unknown Unknowns


Astrophysicist and data scientist Kirk Borne, Ph.D., was among the first to comprehend the importance of vast increases in data as a NASA scientist for almost two decades and now professor of Astrophysics and Computational Science at George Mason University. He’s among the top “influencers” on matters relating to “big data,” And IBM this year named him a…


Added by Ryan Montano on May 15, 2014 at 11:30am — No Comments

Reduce operational costs and improve data driven decision making in Big data Era!

Everyone is talking about data and Big data Whether it’s big or small, simple or complex, freely accessible or locked up in spreadsheets, everyone is worrying about how to get their hands on it . Every company has one or multiple servers, virtual in the cloud, on premise, or both based on the size of the organization. Those servers run applications, websites and other software, which all generate data. only a small amount of people have access to it. Now let me try to explain in simple word…


Added by Prem sah on May 15, 2014 at 8:00am — No Comments

Weekly Digest - May 19

The full version is always published Monday. Starred articles are new additions, posted between Thursday and Sunday

Featured Contributions


Added by Vincent Granville on May 14, 2014 at 6:00pm — No Comments

50 free copies of data science book, signed by the author: get yours!

Fifty copies of my Wiley book are available for the first 50 bloggers posting an original, relevant, non-promotional article, in our blog section.

Your article will be featured in our weekly…


Added by Vincent Granville on May 14, 2014 at 2:00pm — No Comments

The Science News Cycle

Interesting cartoon, epitomizing innumeracy  (or simulated innumeracy). Necessary in today academia to survive and get grants.


Added by Mirko Krivanek on May 13, 2014 at 6:30pm — 1 Comment

Employee Churn 202: Good and Bad Churn

Guest blog post by Pasha Roberts, Chief Scientist, Talent Analytics @pasharoberts

Our prior article on this venue began outlining the business value for solving “the other churn” - employee attrition. We introduced…


Added by Vincent Granville on May 13, 2014 at 9:00am — No Comments

Bad Data Science and Woody Allen

"Life imitates art far more than art imitates life." - Oscar Wilde

In Woody Allen's 1973 iconoclastic movie "Sleeper" a man (health food store owner) wakes up two hundred years in the future. For breakfast…


Added by Michael Walker on May 12, 2014 at 3:00pm — 1 Comment

Business Intelligence Architecture

According to the Asghar et al. (2009), Business Intelligence (BI) is divided into two main parts: (a) BI dimension and (b) BI process. Knowledge, functionality, technology, business and organisation are categorised under BI dimension. The performance of data sources, data warehousing, ETL, OLAPS and other related tools are categorised under BI process. Basically, dimensions and processes are interrelated to form a complete life cycle of BI system…


Added by Avesh Dhakal on May 12, 2014 at 12:30am — No Comments

Addition of Different Dimensions to Data

I was often the lone wolf among my peers in university because I supported a prominent place in society for corporations and an important social role for capital. I questioned whether the directors and executives of companies entered into boardrooms really intending to “oppress” people such as minorities and people with disabilities. Did they deliberately make bathrooms inaccessible to people in wheelchairs perhaps to advance their preconceptions of who gets to go to the bathroom, I pondered…


Added by Don Philip Faithful on May 10, 2014 at 9:44am — No Comments

iPad Program Let's You Touch Your Data


As more devices add touch capabilities, doesn't it make sense that your data should be flexible enough to push around?

Researchers at Carnegie Mellon University may be on to something big when it comes to manipulating Big Data.…


Added by Michael Singer on May 9, 2014 at 1:30pm — No Comments

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