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Power BITrainingTeams

Power BI Team Bootcamp

Your team knows Power BI. But does everyone work from the same foundations?

A practical team training built around the situations your people actually encounter, not a generic tour of Power BI features.

Start with what is actually happening.

  • Capability varies significantly across the team.
  • Different people solve the same modelling problem in different ways.
  • Developers know individual features but lack shared design principles.
  • Training has been topic-based rather than connected to real work.

Good work starts with better questions.

01

What should people be able to do differently after the training?

02

Which mistakes or uncertainties keep repeating?

03

What does “good enough” need to mean for this team?

04

Which practices should become shared standards?

The scope follows the problem.

I do not force every engagement through the same checklist. These are the areas that may matter; the agreed scope determines how deep we go.

Power Query and data preparation

Data modelling and relationships

DAX and calculation design

Semantic-model performance

Report design and user decisions

Power BI Service and lifecycle

Governance and ownership

AI-assisted development workflows

Something you can use after the conversation ends.

The output should help you make a decision, change a practice or move the work forward. It should not exist simply to prove that work happened.

01

Pre-Training Discovery

A short discussion to understand the team, current level and recurring problems.

02

Tailored Agenda

The programme is shaped around the capability you actually need to build.

03

Hands-On Exercises

Participants work through realistic problems rather than only watch demonstrations.

04

Reusable Materials

Reference material and patterns participants can return to after the session.

05

Post-Training Recommendations

Where further practice, standards or support would create the most value.

Enough structure to make the work clear. Not so much process that the process becomes the work.

01

Discovery

We clarify the audience, current level, recurring problems and what people should be able to do differently afterwards.

02

Design

I shape the agenda, examples and exercises around those needs rather than forcing a standard deck onto the team.

03

Live work

The session combines explanation, demonstration, questions and hands-on practice.

04

Follow-through

You leave with material, patterns and clear next steps for applying the learning at work.

The main time commitment is the live live training / workshop. A short discovery conversation happens before delivery so the session can be shaped around the team.

This is likely to help if...

  • Your team already uses Power BI but practice is uneven.
  • You want training connected to your environment and real problems.
  • You care about how people reason, not only whether they can follow clicks.
  • You are looking for a fully self-paced video course.
  • You need formal certification exam preparation only.

If the problem is real but the format is wrong, that is useful to know early. I would rather redirect the conversation than force the challenge into the wrong service.

This does not automatically lead to another engagement.

Sometimes the focused piece of work is enough. If it reveals a useful next step, these are some of the directions that may make sense.

Your team knows Power BI. But does everyone work from the same foundations?

Bring me the problem, not a polished brief. A few sentences about what is happening and what you would like to change are enough to start.

Discuss team training

Send me a message.

You do not need a polished brief. Whether the topic is Power BI, Fabric, AI, team training, mentoring, coaching or simply a challenge that needs untangling, leave a few details and we can start from there.

SIGNALMESSAGECONVERSATION

AI & TRANSPARENCY

AI supports selected parts of my work — it does not replace my judgement, responsibility or relationship with the client.

I use AI tools for tasks such as research, organising information, structuring content and preparing materials. I treat AI as support for my work — not as an autonomous author or decision-maker. Anything I publish or use professionally remains my responsibility.

In coaching, I do not use AI to automatically assess, diagnose or make decisions about a client. AI does not replace attention, confidentiality or human responsibility for the coaching relationship.

AI may support the process. Human responsibility remains.