Build
Custom data and BI training
Reporting and analysis training on your own data and your own reporting stack — so that the output is dashboards people trust, built by the people who need them.
Duration
Two to four days, usually in blocks
Built on
ISO/IEC 27001 · GDPR · ISO/IEC 42001 where AI features are used
Indicative price
On request
Who this is for
Finance or operations manager
Waits days for numbers that then get argued about.
BI or data analyst
Is a bottleneck for requests that others could serve themselves.
CFO or COO
Wants decisions made on one version of the numbers.
Department head
Has a reporting need too small to queue for and too important to skip.
The reports exist. Nobody agrees which one is right.
Most organisations do not have a reporting shortage. They have a reporting surplus: several versions of the same number, built by different people at different times on different definitions, and a quiet consensus that you check with a particular colleague before quoting any of them. The tooling is rarely the cause and it is almost always blamed.
Two things fix it, and only one of them is training. The first is agreed definitions — what a customer is, when revenue counts, which date a month closes on. The second is enough capability in the business that routine questions do not queue behind one analyst. Training without the definitions produces more dashboards that disagree, faster.
So the programme starts with the definitions and teaches on your own data. Participants build reports they actually need, on the stack you actually run, and leave with something in production rather than an exercise file. The people who will maintain a report are the people who built it, which is the only version of this that survives a year.
Where AI features are now embedded in reporting tools — natural language querying, automatic summaries, anomaly flags — the module covers what they are reliable for and where they are confidently wrong, because a plausible summary of a misdefined metric is worse than no summary at all.
How we do it
- 01
Definitions workshop
1 day
The handful of measures everything else depends on, agreed and written down with their owners. Uncomfortable, fast, and the highest-value day in the programme.
- 02
Data landscape
2–3 days
Where the data lives, what is trustworthy, what is duplicated, and what nobody should be building on. Findings given to you in writing.
- 03
Programme design
2 days
Modules by role — consumers who need to read and question a report, and builders who will create them.
- 04
Delivery
2–4 days
On your stack, with your data, building reports people have actually asked for.
- 05
Governance module
within the programme
Who may publish a report, how one gets certified as official, and how the definitions stay current. Without this the sprawl returns within a year.
- 06
Follow-up
30 days
A session once people have built things on their own, which is where the real questions arrive.
Named artefacts
What you receive
- Agreed definitions for the core measures, with named owners
- Data landscape findings, in writing
- Role-differentiated programme for report consumers and report builders
- Working reports built during the programme, on your own stack
- Publishing and certification process for reports
- Guidance on the AI features in your reporting tools — what to trust and what to check
- Attendance and assessment records
- A thirty-day follow-up session
What we need from you
- Access to real data, or a faithful copy. Training on sample data teaches the tool and not the job.
- The people who can settle a definition. Without them the first day produces a discussion rather than a decision.
- A list of reports people actually want. Participants build those, so they exist at the end.
- A decision on who may publish. It is a governance question and it belongs to you.
What changes
- 01One agreed definition per core measure, with an owner.
- 02Routine reporting questions answered in the business rather than queued.
- 03Reports in production at the end of the programme, built by the people who need them.
- 04A publishing process, so the sprawl does not return.
- 05Realistic expectations of the AI features in your reporting tools.
What it costs
On request
All prices exclude VAT.
Questions
Which tools do you teach?
The stack you run. The transferable part is the thinking — definitions, data quality, report design and governance — and the tool is the vehicle for it.
Our data is a mess. Should we fix it first?
Usually not first, and not last either. The programme surfaces exactly which parts of the mess block the reports people actually need, which is a far better remediation list than a general data quality project.
Can this include the AI features in our BI tool?
Yes, and it should. Natural language querying and automatic summarisation are genuinely useful and confidently wrong in specific ways. People need to know which is which before they quote a number in a board pack.
What does it cost?
On request. Scoped on participants, days and whether the data landscape review is included.
Leave with your top three risks documented
Thirty minutes with a senior practitioner. No slideware, no sales engineer.