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Power BIFabricMentoring

Technical Sparring

You do not need someone to build it for you. You need someone experienced to challenge the decision.

One-to-one or small-group technical sparring for difficult Power BI, Fabric and data decisions where the trade-offs matter more than another tutorial.

Start with what is actually happening.

  • You have two technically valid options and no obvious winner.
  • The decision is important but does not justify a formal consulting project.
  • You are too close to the solution and want an external challenge.
  • Senior team members need somewhere to think aloud with another experienced practitioner.

Good work starts with better questions.

01

Should we use Lakehouse or Warehouse?

02

Do we really need Direct Lake here?

03

Should this logic live in DAX or upstream?

04

Is this many-to-many relationship justified?

05

Are we solving the problem at the right layer?

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.

Architecture trade-offs

Semantic-model design

Power BI and Fabric administration decisions

Performance strategy

AI-assisted development choices

Governance boundaries

Solution review

Professional judgement on ambiguous technical problems

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

Focused Conversation

We spend the time on the decision, not on preparing a ceremonial deck.

02

Challenge of Assumptions

I will question the reasoning where the reasoning needs questioning.

03

Trade-Off Analysis

We make consequences explicit instead of pretending there is one universally correct architecture.

04

Recommendation Where Appropriate

Sparring does not mean refusing to have an expert opinion.

05

Optional Follow-Up Notes

A short record of key conclusions when useful.

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

01

Context

We start with a short conversation about what is happening, what matters and what has already been tried.

02

Review

I analyse the relevant parts of the solution or operating model at the depth agreed for the engagement.

03

Prioritise

I organise observations around impact, risk and usefulness — not around how many issues I can find.

04

Walkthrough

We go through the findings together, challenge assumptions and discuss trade-offs.

05

Next step

You decide what happens next: implement internally, continue together or stop because the focused engagement was enough.

I keep the client-side time demand deliberately light. A focused assessment usually needs a kickoff conversation, access or materials, and a final review session. We agree the exact involvement before we start.

This is likely to help if...

  • You already own the problem and need a strong second perspective.
  • You value challenge more than validation.
  • You need expert discussion without a larger consulting engagement.
  • You want somebody else to take full ownership of implementation.
  • You need coaching where I deliberately withhold technical recommendations.

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.

You do not need someone to build it for you. You need someone experienced to challenge the decision.

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.

Tell me what's happening

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.