AI TRAINING
From Data-Poor to Data-Driven in 90 Days
Build a working data stack, live dashboards, and your first AI pilot in 90 days.
What it covers
A structured 90-day programme that takes operations and business leaders from scattered spreadsheets to a functioning data infrastructure. Participants set up a cloud data warehouse, connect core business data sources, build decision-ready dashboards, and launch a scoped AI pilot — all without requiring a dedicated data engineering team. Delivered in three monthly sprints combining live coaching sessions, hands-on lab work, and async self-paced modules. By the end, teams own their stack and can maintain and extend it independently.
What you'll be able to do
- Deploy and configure a cloud data warehouse connected to at least two live business data sources
- Build and publish a dashboard tracking 5+ operational KPIs that non-technical stakeholders use weekly
- Design and document a basic data model that reflects your company's core business entities
- Define, scope, and launch a measurable AI pilot on one repetitive business process
- Establish a lightweight data governance routine — ownership, quality checks, and a change process
Topics covered
- Cloud data warehouse selection and setup (e.g. BigQuery, Snowflake, DuckDB)
- Data source connection and basic ETL/ELT pipelines
- Data modelling fundamentals for business users
- Dashboard design and KPI definition in BI tools (Metabase, Looker, Power BI)
- Data quality, governance basics, and documentation
- Identifying and scoping an AI pilot use case
- Prompt engineering and LLM integration for a business process
- Sustaining data culture: ownership, routines, and iteration
Delivery
Delivered remotely or hybrid over 12 weeks across three monthly sprints. Each sprint includes two 2-hour live group coaching sessions, one individual or team lab session, and async video modules (~3-5 hours). Participants work on their own real company data throughout, with anonymisation support if needed. A shared Slack or Teams channel provides ongoing peer and coach support between sessions. Materials include setup guides, SQL starter kits, dashboard templates, and an AI pilot canvas.
What makes it work
- Executive sponsor who commits to acting on at least one dashboard insight during the programme
- Working with real company data from week one rather than toy datasets
- Dedicating a weekly 30-minute team data review ritual early so the habit forms before the programme ends
- Choosing a narrow, high-frequency AI pilot use case (e.g. invoice categorisation, support triage) with clear success metrics
Common mistakes
- Buying expensive BI tooling before cleaning or centralising source data, leading to dashboards no one trusts
- Scoping the AI pilot too broadly — teams try to automate a complex process before data basics are in place
- Assigning the programme to a single 'data champion' without buy-in from the ops or finance lead who owns the decisions
- Treating the 90 days as a project with an end date rather than the start of an ongoing data practice
When NOT to take this
A company that already has a functioning data warehouse, a BI team, and established reporting pipelines — they need practitioner-level upskilling or an advanced AI engineering track, not foundational infrastructure work.
Providers to consider
Sources
This training is part of a Data & AI catalog built for leaders serious about execution. Take the free diagnostic to see which trainings your team needs.