Case Study: Aktify democratizes data access with dbt Cloud and Databricks
Key results
The challenge
Aktify's conversational-AI insights were hidden in massive data volumes, but complex data dependencies prevented the company from democratizing access. Different users needed data in different forms, from raw data for scientists to pre-aggregated data for executives, and without the right tooling this created bottlenecks. Manual data transformations were slow and error-prone.
The solution
Aktify adopted dbt alongside the Databricks Lakehouse Platform to remove manual effort and risk from its data transformations. The combination let the team stand up new solutions for internal clients quickly and gave stakeholders self-service access to data throughout the organization.
“Databricks Lakehouse Platform and dbt have eliminated the manual tasks and errors from our data transformations. We've been able to stand up new solutions for internal clients in half a day compared to 3-5 days previously.”
BSBrandon SmithDirector of Data and Analytics, Aktify
The results, in context
With dbt and Databricks, Aktify reported an 80% reduction in data engineering hours and a 95% reduction in the time to onboard new employees, plus six-figure annual savings in IT headcount costs. The team could stand up new solutions for internal clients in half a day, compared with 3-5 days previously.