[ COVER OF THE WEEK ]
[ LOCAL EVENTS & SESSIONS]
- Feb 06, 2019 #WEB Online Meetup: Best Practices for Kubernetes
- Feb 22, 2019 #WEB Live-Webinar “Orientierung im Big Data Dschungel” mit Inga Ketels
- Mar 20, 2019 #WEB Insights and Innovation Webinar Series: #3 Big Data for a Better Built Environment
[ AnalyticsWeek BYTES]
[ NEWS BYTES]
[ FEATURED COURSE]
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be ap… more
[ FEATURED READ]
A stimulating excursion into pure mathematics aimed at “the mathematically traumatized,” but great fun for mathematical hobbyists and serious mathematicians as well. Requiring only high school algebra as mathematical bac… more
[ TIPS & TRICKS OF THE WEEK]
Save yourself from zombie apocalypse from unscalable models
One living and breathing zombie in today’s analytical models is the pulsating absence of error bars. Not every model is scalable or holds ground with increasing data. Error bars that is tagged to almost every models should be duly calibrated. As business models rake in more data the error bars keep it sensible and in check. If error bars are not accounted for, we will make our models susceptible to failure leading us to halloween that we never wants to see.
[ DATA SCIENCE Q&A]
Q:You are compiling a report for user content uploaded every month and notice a spike in uploads in October. In particular, a spike in picture uploads. What might you think is the cause of this, and how would you test it?
A: * Halloween pictures?
* Look at uploads in countries that dont observe Halloween as a sort of counter-factual analysis
* Compare uploads mean in October and uploads means with September: hypothesis testing
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
Retailers who leverage the full power of big data could increase their operating margins by as much as 60%.