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Workspace Strategy Sprint

Personal, team, departmental, DEV, TEST, PROD — what should actually go where?

A practical workspace strategy for Power BI and Fabric environments where organic growth has started to make ownership and lifecycle unclear.

Start with what is actually happening.

  • Workspaces were created as needs appeared.
  • Nobody wants to delete anything because ownership is unclear.
  • DEV and PROD are difficult to distinguish.
  • The same team owns unrelated solutions in one workspace.
  • Ownership changes without being reflected in the platform.

Good work starts with better questions.

01

What workspace types do you actually need?

02

How should development and production be separated?

03

Who should own each workspace?

04

How should content move between environments?

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.

Workspace taxonomy

DEV / TEST / PROD patterns

Ownership and administration roles

Naming conventions

Deployment flow

Lifecycle and archive rules

Boundary between personal, team and governed content

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

Workspace Taxonomy

A small number of workspace patterns with a reason for each.

02

Environment Strategy

A pragmatic approach to DEV, TEST and PROD where they add value.

03

Ownership Model

Who owns platform administration, content and business accountability.

04

Naming Convention

Enough consistency to navigate and automate without turning naming into bureaucracy.

05

Lifecycle Guidance

How workspaces are created, reviewed, handed over and retired.

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...

  • Workspace sprawl is starting to make administration difficult.
  • You are introducing deployment pipelines or clearer environment separation.
  • You want a structure that matches how teams actually work.
  • You only have a handful of simple workspaces with clear ownership.
  • You need full enterprise data-domain design beyond Power BI/Fabric workspaces.

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.

Personal, team, departmental, DEV, TEST, PROD — what should actually go where?

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.