Browse Comments — Clean (de-noised)

Dont you dare putting some bullshit title behind just having some common sense. Pls.

Yup! I do this every day!

Truly takes effort from more than just the data team with technical expertise to bring meaningful value to the business from “text written in tabular or whichever format” 💫💯 definitely related to this from my own team’s context, looking forward to the webinar 🙏🏾

But should you not know what Data Steward is even if not in your Title?????

I have been arguing for data stewards foe 20 years, but shortsighted people always shrug it off. Meanwhile, costs pile up!

In the context of AI, informal data stewards are the people catching the problems that models will eventually amplify. The person who documents dataset quirks before they become training data assumptions is doing governance work that no formal review process will surface in time. That behaviour has always mattered, but even more now.

That was the conversation about Rolls Royce, right?

Hannah Cranford, PhD

So true....

Very cool! The voice use case is very tangible. The idea of using smaller model models + more specialization and structure is certainly appealing as well - will be great to see how ELMs can contribute to this!

80% of those working in data governance are grifters, chancers or fly-by-nights. Of those, more than 60% don't even realise they don't know to what extent they are bullshitting the public. Data Governance has become a zero-sum con game, where deceit, fraud and dishonest gaming of the criminally gullible has become the flavour of the day. goodstrat . com

Enrique Marq what scheduling tool are you using to move the content from Claude to the social platforms or is the agent in Claude doing this for you?

Good point, Maarten Masschelein. A lot of companies talk about being data driven, but the real test is simple, who owns the meaning, quality and use of the data once it moves across teams. In practice, stewardship starts when teams treat data as a shared business asset and build the habit of keeping it reliable, clear and usable.

A data steward isn’t just a buzzword, it’s a critical function focused on data governance, quality, consistency, and accountability. Without that foundation, “data-driven” decisions are often just well-dressed assumptions. This reminds me of how casually titles like “Data Analyst” or “Business Intelligence” get handed out. Building spreadsheets and charts is part of the work, but it’s far from the whole picture. These roles require a solid understanding of data modeling, statistics, context, and the discipline to ask the right questions, not just present numbers.

The data steward is such an important role for companies that want to get the most out of their data to scale effectively.

Amin Adatia Fair point no data, no mess. But let’s be honest, no data is a bigger problem than dirty data. At least bad data can be fixed no data means no visibility, no decisions.

Nicole Csintyan Goodwin Laura G. 😂

Coming soon

Recognizing an Organizational Data Steward is a sign of organizational maturity. For this to work, a specific mindset must exist: "Stop fixing bad data; start tuning the process!" The shift from liability to strategic asset only happens when we stop treating data stewardship as a solo role and start seeing it as a collective responsibility. The twist? Everyone who manages a process is a Contributing Data Steward, led by Organizational Data Stewards. Now, for AI to be credible, the accountability must lie with those who feed the model.

Absolutely agree with this. Data stewardship is what turns chaos into clarity — it cleans the “junk drawer” of data, removes the garbage, and makes everything actually usable and insightful. Also not gonna lie, this meme made me laugh harder than it should have 😄