A Data Science Central Community
Contents: three new articles worth reading, posted today; one recently posted and very popular; and a link to our past Thursday digest (at the bottom of this message) if you missed it because of Thanksgiving.
The ABCD's of Business Optimization
I was trying to find some good domain name for our upcoming business science website, when something suddenly became clear to me. Many of us have been confused for a long time about what data science means, how it is different from statistics, machine learning, data mining, or operations research, and the rise of the data scientist light - a new species of coders who call themselves data scientist after a few hours of Python/R training, working on a small project at best, and spending $200 for their training.
Predictive Analytics in the Supply Chain
For quite a long time BI and its ‘current-state’ and historical perspective served quite well. For example, using historical data we could determine that a part takes on average X days to arrive and even calculate standard deviations to make some fairly sophisticated adjustments in our procurement plan. Likewise on the demand side, we could look at historical demand data and try to extrapolate demand into the future, converting that to forecast production requirements and backwards into procurement and logistics requirements.
Great Analysis: HarvardX / MITx Online Courses - Year 1
Online courses are often touted as the savior of higher education, serving as an accessible and affordable alternative to four-year colleges. Proponents point to the accessibility and affordability of online courses; skeptics are quick to note poor completion rates and scant evidence of any clear job market advantage. Using a student-level dataset provided by HarvardX/MITx, I explore the skeptic's former point in the below analysis.
Read full article. The chart below is from this article.
What is Hadoop - An Easy Explanation For Absolutely Anyone
Put simply, Hadoop can be thought of as a set of open source programs and procedures (meaning essentially they are free for anyone to use or modify, with a few exceptions) which anyone can use as the "backbone" of their big data operations.
Finally, you can read our Thursday digest here.