Data tooling is not the problem, processes and people are

Summary — build tools that focus on driving behavioral, process change with Data teams.

  1. Forcing function for education for behavioural change as part of tool adoption and onboarding (e.g. looker modeling language, dbt for workflows).
  2. High investment in “consulting” — e.g. sales engineering, contractors, onboarding to drive behavioral change. Not scalable — but works for some data products.
  3. Filter for organisations/companies that are already data mature (e.g. airbnb — which has a principled data organization) but in this case they are likely doing well with their existing tooling.
  4. Niches which have clearly defined outcomes e.g. funnel analytics with amplitude, crash analytics with crashlytics, sequence analytics with Interana.
  • General purpose data tools are massively adopted (as they are usually at the infra/platform layer — though not necessarily) and their success depends heavily on the organization’s data maturity. The tools have to be exceptionally good at what they do e.g. fivetran or airbyte need to have high coverage of supported sources and sinks or e.g. bigquery needs to be crazy fast with petabytes of data.
  • Behavior change tools examples would include dbt (with their tagline being — “transforming data, transforming teams”), or any BI tool that enables a specific analytics need e.g. amplitude funnel analytics.



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