— In the News —
This 6 minute video from the Wall Street Journal is a stunning look at China's AI experiments in education. For some, it's a kid's worst nightmare. China is "leading" the way here and inevitably, these kinds of experiments will inspire new products and technologies in the West.
— Insight —
It isn’t just that businesses use more software, but that, increasingly, businesses are defined in software. In this post, Jay Kreps, co-founder and CEO of Confluent, explores how that impacts the software architecture of businesses and, in particular, how the data platform is evolving.
A recent McKinsey survey shows that some companies are still dragging their feet with analytics and are increasingly falling behind. But if they're paying attention, the strategies and organizational cultures of the leading companies offer a road map for success.
— Tools and Techniques —
These guidelines by Michael Kaminsky will help you build data models that are more maintainable, more useful, and more performant.
Nice write-up of CFM's automated reporting system using Jupyter notebooks. Covers use-cases, version control, testing, execution and publishing with lots of code snippets and examples.
Randy Au's latest post covers everything you need to know about time, including standards, formats, epochs, key libraries, common pain points, oddities, tips and references. Historical rationale along the way helps explain how we got into this mess.
This guide from the team at Prisma describes the use-cases and structure of a variety of database types, including relational, document, key-value, graph, and wide-column databases. For additional information and resources, check out the corresponding discussion on Hacker News >>
Vettery is an online hiring marketplace that's changing the way people hire and get hired. Ready for a bold career move? Make a free profile, name your salary, and connect with hiring managers from top employers today.
— Resources —
This introduction to common statistical fallacies is easy to follow with examples and links for further info for each fallacy.
— Data Viz —
Forget about the “data-ink ratio.” In this perfectly sized post, Alyssa Fowers explores how much "ink" you really need to make your data understandable.
— Conferences & Events —
Domino Data Science Popup - Chicago - Advance the state of data science within your organization, glean new ideas and technical best practices, and meet like-minded people at the Midwest Data Science Pop-up in Chicago. Don’t miss these practical talks and workshops for data science leaders and practitioners. October 8, 2019