Featured Articles

• Ingredients Of Data Science…

Here I will discuss a general framework to process web traffic data. The concept of Map-Reduce will be naturally introduced. Let's say you want to design a system to score Internet clicks, to measure the chance for a click to convert, or the chance to be fraudulent or un-billable. The data comes from a publisher or ad network; it could be Google. Conversion data is limited and poor (some conversions are tracked,…

Announcement

Predictive Analytics World, March 16-21, 2014 in San Francisco is the business event for predictive analytics professionals, managers and commercial practitioners, covering today's commercial deployment of predictive analytics, across industries and across software vendors. The conference delivers…

Here are my reactions to the LinkedIn conversation about the "Statistical data scientists". In short, I believe that modern big data needs new ways of processing data, and that data scientists are polyvalent (versatile) with deep expertise in a few domains, across…

Featured Articles

• Why Companies can't find analytic talent…

Business analysts focus on data base design (database modeling, at a high level, including defining metrics, dashboard design, retrieving and producing executive reports and designing alarm systems), ROI assessment on various business projects and expenditures, and budget issues. Some work on marketing or finance planning and optimization, and risk management. Many work on high-level project management,…

One of the main differences between a data scientist and a data engineer has to do with ETL versus DAD:

• ETL (Extract/Load/Transform) is for data engineers, or sometimes data architects or database administrators (DBA).…

I recently had the following discussions with a number of data architects, in different communities, in particular (but not limited to) the TDWI group on LinkedIn. This is a summary of the discussion, featuring differences between data scientists and data architects, and how both can work together.

It…

Many statisticians think that data science is about analyzing data, but it is more than that. Data science also involves implementing algorithms that process data automatically, to provide automated predictions and actions, such as:

• Automated bidding systems…

We are now at 9 categories after a few updates. Just like there are a few categories of statisticians (biostatisticians, statisticians, econometricians, operations research specialists, actuaries) or business analysts (marketing-oriented, product-oriented, finance-oriented, etc.) we have different categories of data scientists. First, many data scientists have a job title different from data scientist, mine…

Enjoy the reading!

• Data scientists work at Starbucks, but they’re not everywhere just yet…

Featured Articles

• 14 articles and resources worth reading…

Looks like a new association recently created. Their resource section (see extract below) looks very interesting.…

Interesting article. I have the same point of view, had the same problem and did the same thing:  

Provost noticed during his data classes that there weren’t any books he could recommend to his MBA students that taught the fundamental principles. They were either too granular and focused on the math, or else too…