The Data Warrior

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

Archive for the tag “thought leadership”

Data Vault and Data Mesh – A Match Made in the Cloud?

Check out my latest thoughts about Data Vault and Data Mesh:

Over the last six years (after I joined Snowflake basically), I have witnessed a massive increase in the interest and implementation of Data Vault 2.0. I have talked to literally hundreds of companies across the globe and across all industries about changing their approach to building an enterprise data platform. It was sort of mind boggling how many folks wanted to speak to me about this. So why, after almost two decades of successful data vault implementations, have so many people “suddenly” got interested in Data Vault?

Well, a few reasons:

1. They are moving to the cloud (in this case, Snowflake) and figured it was time to look at their approach to data warehousing and data lakes.

2. What they had been doing for decades, on critical review, really was not working (i.e., lots of expensive re-engineering all the time) and definitely could not scale.

3. Things are changing so rapidly, they needed to find a way to be more agile.

Read the rest of the post here on the Data Rebels site to find out how Data Vault relates to Data Mesh – Data Vault and Data Mesh

What do you think?

Have a great week!

Kent

The Data Warrior

Life and Times of The Data Warrior

Please join me on March 30th at 11AM CDT for my first official post-retirement talk!

I will be chatting with Mike Lampa from Great Data Minds about my career and plans post-Snowflake. I expect we will cover a wide range of topics including what community and technical evangelism is all about, as well as what made me jump from nearly 30 years in the Oracle world to a small startup with less than 100 people that claimed to have re-invented data warehousing in the cloud.

You can register here for this free event.

See you then!

Kent

The Data Warrior

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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