𝗗𝗼𝗻'𝘁 𝘁𝗿𝘂𝘀𝘁 𝘁𝗵𝗲 𝗵𝘆𝗽𝗲. 𝗪𝗲 𝗱𝗼𝗻'𝘁 𝗮𝗹𝘄𝗮𝘆𝘀 𝗻𝗲𝗲𝗱 𝗮 𝗳𝗲𝗱𝗲�...

𝗗𝗼𝗻'𝘁 𝘁𝗿𝘂𝘀𝘁 𝘁𝗵𝗲 𝗵𝘆𝗽𝗲. 𝗪𝗲 𝗱𝗼𝗻'𝘁 𝗮𝗹𝘄𝗮𝘆𝘀 𝗻𝗲𝗲𝗱 𝗮 𝗳𝗲𝗱𝗲𝗿𝗮𝘁𝗲𝗱 𝗺𝗼𝗱𝗲𝗹.

Everyone seems to recommend federated governance. Over the last few years, it has become the model everyone talks about. But that doesn't mean it's the right choice for every organization.

The right model depends on your maturity, your organization and the problems you're trying to solve.

A 𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗺𝗼𝗱𝗲𝗹 usually works best when governance is new, regulations are strict, data quality is inconsistent or ownership is still unclear. It helps create common standards, shared definitions and consistent ways of working.

Raj Gupta Completely agree. Centralization gets a bad reputation for being slow, but it’s essential for building a baseline of trust and standards. You can't distribute ownership to domains that aren't mature enough to handle the responsibility yet.

KOMAL CHHEDA There's a point many teams miss, Mathieu. Decentralization only works when accountability is already part of the culture. Without that, you're not distributing ownership, you're distributing confusion.

tgroenwals shared this post · Jul 1

Mathieu Le Guével

Jun 30 · archived Jul 1

𝗠𝗼𝘀𝘁 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗱𝗼𝗻'𝘁 𝗵𝗮𝘃𝗲 𝗮 𝗱𝗮𝘁𝗮 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆... 𝗧𝗵𝗲𝘆...

𝗠𝗼𝘀𝘁 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗱𝗼𝗻'𝘁 𝗵𝗮𝘃𝗲 𝗮 𝗱𝗮𝘁𝗮 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆... 𝗧𝗵𝗲𝘆 𝗵𝗮𝘃𝗲 𝗮 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗿𝗼𝗮𝗱𝗺𝗮𝗽.

I often see organizations investing in cloud platforms, AI and modern data stacks before answering a much simpler question.

What business problem are we trying to solve?

A data strategy defines where the company wants to create value with data. Data governance makes that strategy executable.

Without governance, priorities stay unclear.
↳ Ownership is missing.
↳ Data quality depends on individual effort.
↳ Teams move in different directions.

Rizwan Tufail Technology roadmaps are easier to fund, but governance is the layer that makes data reliable. Without named owners, even strong platforms turn into scattered efforts.

Hanan Al Rabiee This resonates. In my experience, organizations often rush to discuss platforms, dashboards, or AI before defining the business problem they’re trying to solve. Once the business objective is clear, strategy, governance, and technology naturally fall into place.

tgroenwals shared this post · Jun 6

Mathieu Le Guével

Jun 4 · archived Jun 4

𝗚𝗼𝗼𝗱 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘇𝗲 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗯𝘆 𝗱𝗲𝘀𝗶𝗴𝗻.
I still see many companies separating both worlds. The platform team focuses on pipelines, storage, APIs and cloud scalability.

The governance team works on ownership, policies, definitions and compliance.
Then trust issues appear everywhere.
↳ Who owns the KPI?
↳ Why does the dashboard change every week?
↳ Which dataset is reliable for AI?
↳ Who approved this access?

The problem is not always the tooling.

Alejandro Giraldo Henao This infographic is gold. Thanks for sharing Mathieu Le Guével Jun 4 1 like

Reeves Smith Practical governance drives real behavior, not just policy compliance. Jun 4 1 like

tgroenwals shared this post · Jun 3

Mathieu Le Guével

Jun 3 · archived Jun 3

𝗬𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗶𝘀 𝗻𝗼𝘁 𝘆𝗼𝘂𝗿 𝗱𝗮𝘁𝗮 𝗱𝗼𝗺𝗮𝗶𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆.

I keep seeing companies investing heavily in modern data platforms while ownership stays completely unclear underneath.

On one client mission, the technical foundation was honestly solid. The catalog was connected, lineage existed, governance workflows were running and teams could already access a lot of data.

Yet every governance discussion turned into the same problem:
↳ Who decides?
↳ Who owns customer profitability?
↳ Who validates KPI definitions?
↳ Who arbitrates when two teams calculate the same metric differently?

Gururaj R J This is a key gap many organizations miss platform maturity without domain accountability.
Governance only works when ownership is embedded in business domains, not just tools.
Jun 3

Reeves Smith The fastest way to resolve a metric dispute is knowing who owns the definition. Jun 3 1 like

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𝗗𝗼𝗻'𝘁 𝘁𝗿𝘂𝘀𝘁 𝘁𝗵𝗲 𝗵𝘆𝗽𝗲. 𝗪𝗲 𝗱𝗼𝗻'𝘁 𝗮𝗹𝘄𝗮𝘆𝘀 𝗻𝗲𝗲𝗱 𝗮 𝗳𝗲𝗱𝗲�...

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