archive.Joe Lamantia.com

I’ve posted a substantial readout summarizing some of the more salient findings from a long-running programmatic research program into data science. This deck shares synthesized findings around many of the facets of data science as a discipline, including practices, workflow, tools, org models, skills, etc. This readout distills a very wide range of inputs, including; direct interviews, field-based ethnography, community participation (real-world and on-line), secondary research from industry and academic sources, analysis of hiring and investment activity in data science over several years, descriptive and definitional artifacts authored by practitioners / analysts / educators, and other external actors, media coverage of data science, historical antecedents, the structure and evolution of professional disciplines, and even more.

I consider it a sort of business-anthropology-style investigation of data science, conducted from the viewpoint of product making’s primary aspects; strategy, management, design, and delivery.

I learned a great deal during the course of this effort, and expect to continue to learn, as data science will continue to evolve rapidly for the next several years.

Data science practitioners looking at this material are invited to provide feedback about where these materials are accurate or inaccurate, and most especially about what is missing, and what is coming next for this very exciting field.