All Hands on Data #95
Extra! Extra! Read all about it! Whether you're ramping up after Q1 or looking to close out Q2 strong, a break is much needed. Grab your coffee and catch up what's happening in data this week!
Article Recommendations
YAML developers and the declarative data platforms
The author does a great job laying out how languages like YAML have made a significant home in the data engineering space. Declarative paradigms, inspired by SQL, are something that can be rapidly intuited and implemented by old and new engineers alike. Now only if Shipyard had something like that... (https://www.shipyardapp.com/docs/blueprint-library/google-bigquery/google-bigquery-execute-query/#yaml) - John Forstmeier
People and Python in AI
This article touches on industry trends, programming literacy, and the practical use of common tools to enhance data-driven decision-making. The article also addresses the cultural challenges organizations face in becoming truly data-driven, an important consideration for anyone in the field. - Johnathan Rodriguez
Unlocking The Power of Analytics: How To Adopt A Data-Driven Mindset
We always talk about data tools and best practices but one of the biggest hurdles a lot of companies (even people) face is having a data-driven mindset. You can have the best tools in the industry but if the way you tackle problems relies more on "gut feel" than data, these tools are essentially useless. This article walks through how to change your mindset to ensuring data is at the forefront of every problem being solved. - Angel Catalan
Data-as-a-Product and Data-Contract: An evolutionary approach to data maturity
Olivier took a novel approach to finding the tipping point of when an organization should actually start caring about data mesh and data contracts by relating the stages of data maturity to Wardley's evolution model. He posits that once a dataset drives more than one use case internally, the need to apply product thinking to the data increases greatly, especially if the data needs to be trusted by multiple stakeholders. - Blake Burch
Podcast Recommendations
Machine Learning Street Talk (MLST) - Prof. Chris Bishop's NEW Deep Learning Textbook!
In this fascinating episode, pioneering machine learning researcher Chris Bishop discusses the past, present, and future of AI and deep learning. He shares insights on inductive bias, scientific applications, and the continuing mystery of why deep learning works so well.
R Weekly Highlights
This week's R Weekly podcast discusses troubleshooting CRAN build failures, new features in the WebR platform like better graphics and error handling, and an excellent blog post with animated visuals explaining tidyverse data wrangling functions.