06-reference

joe reis state of data modeling april 2026

Mon Apr 13 2026 20:00:00 GMT-0400 (Eastern Daylight Time) ·reference ·source: Practical Data Modeling (Substack) ·by Joe Reis

State of Data Modeling — April 2026 Pulse Survey (Joe Reis)

Why this is in the vault

Joe Reis is one of the highest-signal voices in our niche — co-author of Fundamentals of Data Engineering, originator of DEDP (Data Engineering Design Patterns) that we have extensive chapter notes on, and author of the ongoing Making Models Awesome (MMA) series we’ve been processing weekly. This post is short (a survey teaser, not a full essay) but it carries one load-bearing market signal worth filing.

The post itself is a call to take a 6-question follow-up survey; findings will be presented at his Stockholm keynote May 7. Worth tracking so we can re-file the results post when it drops.

Key findings from survey (cited prior wave)

Reis references the Practical Data Community 2026 survey as the baseline he’s drilling into:

That’s the entirety of the quantitative content in this issue. The rest is logistics (survey link, Stockholm keynote reference).

Mapping against Ray Data Co

The ~90% pain-point figure directly confirms the MAC thesis. If the overwhelming majority of practitioners are admitting modeling pain out loud in a public survey, the addressable market for a structured “definition of done” framework is the entire field, not a niche. This is the clearest external data point we’ve logged that says MAC is not solving a boutique problem.

Three concrete implications:

  1. MAC content series positioning — Reis’ three probe areas (ownership, standards, decay-over-time) are the exact wedges MAC addresses. The testing matrix is fundamentally a standards artifact that clarifies ownership and decay prevention. The Sanity Check editorial calendar should have at least one issue per probe area, timed to piggyback on Reis’ Stockholm keynote publicity (May 7).

  2. ADWD (Corr) cross-reference — The Corr methodology we finished processing yesterday (book-adwd-master-synthesis-2026-04-13) is BEAM-first requirements gathering. BEAM is literally a tool for establishing ownership and standards at modeling time. If Reis’ survey finds ownership ambiguity as a top pain point, BEAM event-matrix workshops are a direct consulting offer we can package.

  3. Consulting niche positioning — The decay-over-time question is particularly valuable. Most data quality tooling (Monte Carlo, etc.) detects decay after the fact. MAC is upstream — it prevents the decay by making the definition of done explicit at build time. That’s a defensible positioning against observability-only competitors.

Action for the board: Add a task to re-process the Stockholm keynote findings when Reis publishes them (estimate: mid-May 2026). Those findings will be the single best external validation (or falsification) of the MAC thesis we’ll get this quarter.

Challenge to our thesis: Nothing yet — this is a signal-gathering issue, not a conclusions issue. Worth watching whether Reis’ findings emphasize tooling gaps (our lane) or org/political gaps (see 2026-02-04-practical-data-modeling-organizational-dynamics, which leans political). If Stockholm findings say “modeling decays because of org politics, not technique,” MAC needs a complementary org-change narrative, not just the matrix.