Taxonomy v Folksonomy

The concepts of taxonomy and folksonomy hold significant implications, especially in the context of emerging technologies like OpenAI. While traditional taxonomies offer structured hierarchies of knowledge, allowing for a systematic approach to information organization, folksonomies represent a more fluid and emergent way of categorizing information based on user-generated tags and metadata.

However, the challenge arises when technological advancements fail to incorporate divergent thinking and promote groupthink through convergent taxonomies. This phenomenon is particularly evident in language models, where developers' linguistic and cultural biases can influence the interpretation and representation of (the dominant) language.

To code or not to code? The value of Domain Knowledge in Data Teams

A little while ago, I chatted with Gartner Analyst David Pidsely about a trend I noticed in the job market. It seemed the last 2-3 years, data strategy and governance roles suddenly required coding experience.

It wasn’t my imagination, he confirmed. In 2023, skills and talent shortage were the number one inhibitor to CDAO success. Hiring managers and recruiters have been packing job descriptions with coding skills that don’t always require them.

Data Trend: From Spreadsheets to Algorithms

The transition from traditional spreadsheets to sophisticated data management and analysis algorithms represents a significant evolution that has revolutionized how businesses process and leverage information. Algorithms have reshaped the landscape of data-driven decision-making. Facebook's filter bubble is an early example of a machine learning system individualizing the user experience based on user patterns.