The Data Warrior

Changing the world, one data model at a time. How can I help you?

Archive for the tag “thought leadership”

Data Mesh Learning – Interview with The Data Warrior

Last week I had the privilege of being interviewed by Nick Heudecker (former Gartner analyst and current Senior Director at Cribl) for the Data Mesh Learning Community. In our interview, we covered the idea of empowering business domains to really own and manage their data via things like templates and a center of excellence, not to just give them the responsibility of owning their data and leaving them to figure the rest out on their own. We also discussed the need for organizations to focus on investing in growing a data culture, not just investing in the newest cloud based tooling. Really, how do we lower the barriers to accessing, sharing, and leveraging data and get people to really think about data-as-a-product.

Like Agile before it, Data Mesh is as much about changing the way an organization thinks and works as it is about technology. I argue that the people and organization aspects of adopting a data mesh approach are more important than the technology aspects. Without the right approach, the best technology (like Snowflake), is not going to solve your organization’s data problems.

See the full interview here:

So what do you think about all this data mesh stuff?

Cheers!

Kent

The Data Warrior

P.S. For much more on the thoughts about #datamesh, check the other podcasts and videos listed on my Snowflake Resources page.

A New Ethics of AI

In my latest post I tackle one of those current hot topics – Ethics (and bias) in AI and machine learning.

People tend to simplify. So all types of machine-assisted thinking get dubbed “artificial intelligence,” or AI.

What we’re really talking about with AI or machine learning is an algorithmic approach to analysis: We’re going to look at a bunch of data, and artificial intelligence is going to help us figure some things out. It’s going to tell us things we would have a difficult time finding ourselves.

Here’s where machine learning comes in. It’s all about training a model. When we speak about a model we’re really just talking about code. It’s a coded algorithm—a coded set. A statistical model is the other term for it. So for the data architects of the world, when we think of a data model, we’re thinking of tables, columns, and relationships. In the simplest form, however, we’re talking about a specific set of data.

Check out my thoughts on how we can try to deal with ethics and bias here: A New Ethics of AI

What do you think about this topic?

Cheers!

Kent

The Data Warrior

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