Benchmarks · Analytics engineering and data-team survey
Research data-team priorities, governance and quality pain, analytics-engineering workflows, and buying triggers for transformation, catalog, testing, and data-product tools. This is unusually close to the target market: data practitioners shipping governed, reusable analytics and data products.
Put it to work
Research data-team priorities, governance and quality pain, analytics-engineering workflows, and buying triggers for transformation, catalog, testing, and data-product tools. This is unusually close to the target market: data practitioners shipping governed, reusable analytics and data products.
Match the published cohort and metric definition to your company before comparing results. Use a gap to choose a question to investigate with your own data.
What it covers
Geography: Use the geography stated by the source; coverage can vary by dataset and release.
Granularity: Research data-team priorities, governance and quality pain, analytics-engineering workflows, and buying triggers for transformation, catalog, testing, and data-product tools.
Source type: Analytics engineering and data-team survey
Access and cost
Public official report page describing the research; the page presents a report download, which may require a contact form.
Cost: Current price was not established in this review; check the provider's access terms.
Update cadence: Release cadence was not normalized in this review; check the source's dates, update notes, and API limits before comparing periods.
Before you use it
Publisher sponsorship and the dbt-centered analytics-engineering audience may bias tool/workflow representation; do not treat it as a census of all data teams.