Databricks wants a clearer view of how users engage with the platform across workspace activity, SQL usage, notebook collaboration, and trial-to-paid conversion. The VP of Marketing asks you to use product interaction data to identify the most important trends from the last two quarters and explain which ones matter for pipeline growth and customer expansion.
You are given six months of event-level data for 420,000 registered users across free trials, self-serve accounts, and enterprise workspaces. In the latest quarter, weekly active users grew from 118,000 to 131,000 (+11%), but trial-to-paid conversion fell from 8.4% to 6.9%, 8-week retention for new trial users dropped from 31% to 24%, and average notebooks run per active workspace declined from 14.2 to 12.6. At the same time, Databricks SQL query volume increased 18%, and the share of users interacting with Delta Live Tables rose from 9% to 15%.
Stakeholders want to know whether overall engagement is actually improving, which user segments are driving the changes, and where marketing should focus acquisition and lifecycle programs.
user_events: event_timestamp, user_id, account_id, workspace_id, event_name, product_surface, session_id, device_typeaccounts: account_id, account_type, industry, region, contract_start_date, plan_tiertrial_funnel: user_id, acquisition_channel, trial_start_date, activation_date, paid_conversion_dateworkspace_usage_daily: workspace_id, date, notebooks_run, sql_queries, jobs_triggered, dlt_pipeline_runs, active_usersuser_profile: user_id, persona, company_size, country, signup_date