Departmental programme · Data & Analytics
Analysis. Dashboards. Data Storytelling.
Turn business data into insight faster with AI-assisted analysis and reporting workflows your stakeholders actually use.
01 · Overview
Data only helps when it reaches decisions. This programme trains your analysts to use AI for faster analysis, then designs, builds and launches AI-assisted analysis and reporting workflows — from data preparation to insight summaries — with checks for accuracy.
Target outcome
AI-assisted analysis and reporting workflows in daily use, delivering clearer insight with built-in accuracy checks.
This departmental programme adapts the core 90-Day AI Transformation framework to the work of this team. The curriculum is a proposed adaptation and is finalised with you during discovery. See the core framework.
02 · Is this for you?
03 · Skills
04 · Your 90 days
Five stages. Training and optional implementation consultation run side by side: Learn → Design → Build → Launch → Support.
Stage 01 · Weeks 1–3
We start by listening. Your team learns to use AI well and safely on everyday work, while discovery runs alongside to find where AI can make the biggest difference.
See Module 1: AI-Powered Data Productivity05 · Curriculum
Each 2-day module builds on the one before. Every exercise uses your team's real work — no coding needed.
Module 1 of 4 2 days · Week 2
AI basics for everyday analytics work
Everyone starts on the same page. Your analytics team learns what generative AI can and can't do, and how to get reliable results on real work such as data cleaning, formulas, trend analysis and insight summaries. Good habits come early: checking answers, protecting business and customer data and saving the best prompts as templates the whole team can reuse.
Hands-on exerciseComplete one real analytics task faster with AI and compare it with how it's done today.
What learners walk away with
Day 1
Using AI well
Day 2
Documents and good habits
Module 2 of 4 2 days · Week 4
Find the problem, design the fix
Good AI tools start with the right problem. Teams map how a recurring reporting request really works — where time is lost, where mistakes creep in and where people wait on each other — and decide which steps suit AI, simple automation or a person. Day 2 is a guided, no-code hackathon where small teams turn the best ideas, such as an insight summariser or a data-question assistant, into early working versions.
Hands-on exerciseHackathon: build and demo an early working version of a analytics tool.
What learners walk away with
Day 1
Find and plan the fix
Day 2
Hackathon day
Module 3 of 4 2 days · Week 6
Build your AI tools together
Now the real building starts. Using no-code and low-code tools suited to your team, learners turn the chosen ideas into working AI tools for analytics work. The work is shared out so everyone contributes: some set up the screens, some write the instructions and reference material, others build the approval steps and test cases.
Hands-on exerciseBuild and test a working version of your chosen analytics tool on real cases.
What learners walk away with
Day 1
Build the core
Day 2
Connect and test
Module 4 of 4 2 days · Week 10
Launch them and look after them
A tool only pays off if people use it and it keeps working. Learners test their analytics tools on real scenarios, decide who can access what and plan for when something breaks — then learn the routines that keep AI tools useful: tracking usage, updating reference material, training colleagues and measuring report turnaround and stakeholder use.
Hands-on exerciseRehearse the launch and write the how-to guide your colleagues will use.
What learners walk away with
Day 1
Test and get ready
Day 2
Run and improve
06 · Applications
Examples only. What your team builds is chosen together from your own shortlist of problems.
07 · How it's delivered
Four hands-on, 2-day modules — 8 training days in total. Each module builds on the one before, using your team's real work.
Optional consultation runs alongside the training to help you choose, build and launch the right solutions. Scope is agreed in your proposal.
Programme structure is indicative. Consultation scope, cohort size, support period, tools to be built and commercial terms are confirmed in your proposal. Course titles do not imply accreditation or funding eligibility.
08 · Deliverables
Tools launch once they pass final testing. If one isn't ready, you get a clear plan to finish it.
Tell us about your team and goals. We'll shape the 90-Day AI Transformation for Data & Analytics Teams around your work and confirm scope in a proposal.
Quick chat
See if it's a good fit for your business.
Pick your team
The boss, a core team and the learners.
We start
Discovery begins in Week 1.