All Hands on Data #55
Welcome to week 55 of All Hands on Data! Check out our team's favorite articles from the past week covering the data industry below.
AI and Big Data Analytics in Retail Industry
Speaks about how AI is transforming the retail space. Everything from personalize marketing and promotions to affecting the supply chain management - Johnathan Rodriguez
Mastering Data Collection and Analysis in the Era of Cloud Native Applications
The post highlights six major considerations when working in the cloud data space. While all are important, the first one, "Prioritize Data Relevance", is the most important. Although data costs are low, mental overhead is not - forcing a team to pull down any and all data is a waste of time and effort. Focus on a few things and do them well. - John Forstmeier
3 Ways to Enhance Data Transparency
It gives an interesting point of view on how you can make data more accessible to members of a company while not compromising and privacy or security. - Angel Catalan
Why Mojo
I'm always interested by new languages that rise to the surface, and Mojo has peaked my interest not just because of the gaudy performance gains (35,000x improvement over Python in some benchmarks) but also because as a Julia enthusiast, I feel the problem that Mojo is addressing has been tackled by Julia. That being said, the fact that Mojo will be a superset of Python is a strong selling point and lowers the barrier of entry substantially. - Wes Poulsen
How Media Leverage Innumeracy to Create Click-bait
Data equals truth, truth equals fact, and facts equal a clear-cut conclusion, right? Wrong. This article points out a very specific example of how news outlets and statisticians can use truthful data points to get to misleading conclusions. While the article is talking about the weather, the author goes on to show how this one occurrence is actually an example of media using data points for misleading conclusions and click-bait articles. Sure it might seem that something is record-breaking but when you get into the weeds of the data, it might turn out that the one data point isn't statistically significant at all. - Reed Cowan
Black Swans & People Analytics
This article challenges the notion that prediction is everything. It emphasizes testing accuracy, adopting a mindset of thinking in bets, and continuous improvement. The question arises: if one knew of a coming "unpredictable" event while others didn't, should they inform the masses or keep it to themselves? - Arynn Martin-Post