Data Conference Databasea Query.Farm index
Companies

Dataroots

Product category (jev): unsure; best guess “Data providers” at 35% confidence, so it isn't used in filters or charts
Org type (jev): Software vendor 69% confident
Conferences sponsored0
Events sponsored0
Speaker slots73 distinct people
Conferences present at5sponsor or speaker
Years active2022–2025

Circuit mix

Where Dataroots shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.

Presence by conference and year

Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.

  • Title
  • Platinum
  • Gold
  • Silver
  • Bronze
  • Other / unlabeled tier
  • Had speakers

Activity by year

Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.

Conferences present at

Distinct conferences each year, split by whether the company sponsored or only had speakers there.

  • Sponsored
  • Speakers only

Distinct speakers

People from this company on a program that year, each counted once.

Where they've grown or pulled back

Dataroots has never sponsored a tracked conference, so this follows where its speakers appear instead.

DownNothing recorded in 2026; had speakers at 2 conferences in 2023.

Counted per conference. 2026 is the latest year whose conferences have mostly happened. A conference counts as no longer seen only when later events published speaker lists.

New conferences spoken at 1

First speaker in 2025 or later.

No longer seen 4

No speakers since 2024 or earlier, though the conference published speaker lists after that.

Lookalikes

Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).

  1. MLJAR0.74
  2. DevITJobs0.74
  3. Cubist Systematic Strategies0.73
  4. Klarna0.70
  5. Streamlit0.69
  6. Python Software Foundation0.68
  7. ASML0.68
  8. Octopus Energy0.67

16 Cluster: PyCon · EuroPython circuit →

Often sponsors alongside

Companies that sponsored the same events, by number of shared events (out of 0 this company sponsored).

No co-sponsors: this company has no recorded sponsorships, or sponsored alone.

Neighborhood: companies with nearby conference footprints

Dataroots (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.

DatarootsDevITJobsCubist Systematic StrategiesMLJARKlarnaPython Software FoundationRecursionYDataBCGJetBrainsUniversity of CopenhagenOctopus EnergyFeedzaiStreamlitPloomberNumFOCUSUniversity of British ColumbiaBluevinePacktOrdina PythoneersMozillaUniversity of Southern CaliforniaManningOpenTeamsParity TechnologiesQuansightEpisourceTaipySpace Telescope Science InstituteWarsaw University of TechnologyKiwi.com
DatarootsDevITJobsMLJARKlarnaPython Software FoundationRecursionYDataBCGJetBrainsUniversity of CopenhagenOctopus EnergyFeedzaiStreamlitPloomberNumFOCUSUniversity of British ColumbiaBluevinePacktMozillaManningOpenTeamsParity TechnologiesQuansightEpisourceTaipyKiwi.com

Sponsorships 0

No sponsorships recorded for Dataroots.

Speakers 7

SpeakerEventRoleTalkLinks
Dorian Van den HeedeSQLBits 2025speaker🎲 Your best Bet: Effortless MLOps with dbt—
Sam DebruynData Saturday #59 - Data Saturday Holland 2024speakerFabric Capacities: Divide and Conquer—
Sam DebruynData Saturday #59 - Data Saturday Holland 2024speakerMedallion for Data Mesh: Exploring Workspace, Capacity, and Domain Design in Microsoft Fabric—
Dorian Van den HeedePyData Eindhoven 2023talkYour best Bet: Effortless MLOps with Python Models in dbtVideo
Sam DebruynData Platform Next Step 2023talkdbt & Fabric: better togetherSlides
Murilo CunhaPyCon Ireland 2022talkEffective data science teams with databooks—
Murilo CunhaPyCon JP 2022talkEffective data science teams with Jupyter and databooks—