The Data Warrior

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

Archive for the category “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

Mass Data Fragmentation: Reducing ‘Data Puddles’

Shortly before leaving Snowflake last year, I was interviewed for this post about one of the worst case examples of data siloes I had seen – we called them data puddles!

A few years ago, Kent Graziano joined a big organization to work on its data. The first problem was that nobody really knew what and where all the data was. Graziano took his first three months on the job investigating data sources and targets, ultimately creating an enterprise data map to illustrate all the flows. It wasn’t pretty.

“In the end, I discovered that the same data was being sent to three or four places,” he said. In one case raw data was transformed and stored in a data warehouse, then moved from there into another warehouse—which was also pulling in the original raw data.

Graziano, who recently retired from his post as Chief Technical Evangelist at Snowflake, said this scenario is entirely common. Data scattered and copied in lakes, warehouses, data marts, SaaS platforms, spreadsheets, test systems, and more. That’s mass data fragmentation, or, more colloquially, data sprawl or data puddles. 

Indeed, 75% of organizations do not have a complete architecture in place to manage an end-to-end set of data activities including integration, access, governance, and protection, according to IDC’s State of the CDO research, December 2021. This lack of governance combines with legacy systems, shadow IT, and good intentions to pave the road to a lot of fragmentation.

Check out the rest of the post to learn how data sprawl hurts businesses and what to do about it. Read it all here!

Try not to step into any of those puddles!

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.

Post Navigation

%d bloggers like this: