The Data Warrior

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

Archive for the category “thought leadership”

The Data Warrior Way – DataOps: Past, Present, and Future

Heads up gang – I will be doing a webinar on #TrueDataOps on Wednesday, Nov 30th!

4 pm UTC – 10 am CDT, 11 am ET, 4 pm London, 5 pm CET

During this 60-minute live webinar, I will delve deeper into this topic to share my thoughts on DataOps. What is it? How is it different from DevOps? Where is it headed?

Join me to learn about the seven key pillars of #TrueDataOps:

  • ELT and the spirit of ELT
  • Continuous Integration / Continuous Deployment (CI/CD)
  • Code design and maintainability
  • Environment management
  • Governance and change control
  • Automated testing and monitoring
  • Collaboration and self-service

Come learn what DataOps REALLY IS, and how it’s guiding philosophy can help you deliver data projects faster and better.​

Sign up today to reserve you space! (Yes – it will be recorded!)

The Data Warrior Way – DataOps: Past, Present, and Future | WhereScape

See you there!

Kent

The Data Warrior

The Hype:  Data Mesh Will Become Obsolete – Really?

Data Mesh is indeed a hot topic these days. Is it the answer to all our big data problems? Probably not, but it will help some organizations. Is it obsolete? See what I think in this recent blog post…

In the summer of 2022, Gartner® published its Hype Cycle on Data Management, and this was not without some controversy.

In particular, it asserted that Data Mesh will be obsolete before it reaches what Gartner calls the Plateau of Productivity. It is hard to fathom how they came to that conclusion when there is such a vibrant Data Mesh Community complete with a very active Slack channel, and when DataOps.live customers like Roche and OneWeb have successfully built a Data Mesh using DataOps.live and Snowflake. But we’ll come back to that in a moment.

Data Mesh is in essence a conceptual approach and architectural framework, not a specific off-the-shelf tool or technology. One of the main precepts for its creation is angled towards improving productivity and time to value by eliminating the perceived bottlenecks that have been experienced by organizations building out large-scale enterprise data warehouses and data lakes.  Zhamak Deghani, the creator of the Data Mesh concept, has referred to it as a decentralized sociotechnical approach – meaning it involves people, processes and technology. So, it seems likely that no two implementations will be the same by their nature. How one organization defines productivity based on its specific needs and outputs on its own application of Data Mesh will differ from another. Yes, Data Mesh is (kind of) new and yes, it is maturing, but that does not mean we should ignore or discount it this early in the game.

It is hard these days to separate the hype from the reality so check out the entire post over at the DataOps.live blog.

Cheers.

Kent

The Data Warrior

How Data Vault 2.0 Supports Your Data Governance Strategy – Part 1

Data Vault 2.0 is way more than just a data modeling approach. In fact it is an entire methodology and architecture for building business intelligence and analytic solutions. This is a post just released that I wrote for Data Rebels on how DV2 actually supports various aspects of data governance. Check it out.

With the growth of volume and diversity of data in recent years, it has become even more critical for organizations to develop an effective and scalable strategy for data governance and its closely aligned sibling discipline – Master Data Management. The importance of ensuring the security and the quality of data has never been more important than now. Add to that the increased pressures for regulatory compliance and privacy concerns, having a solid approach to data governance is no longer an option, it’s a necessity. In this 2-part blog series, I will discuss how the Data Vault 2.0 System of Business Intelligence addresses these concerns and incorporates both Data Governance and Master Data Management. 

Read the entire post here: Data Vault 2.0 and Data Governance – Part 1.

Stay tuned for Part 2!

Kent

The Data Warrior

To Train or Not to Train – Is That Still a Question?

For years I have been an advocate for training, of all kinds. In my recent post for DataRebels, I dicuss the pros and cons of getting trained along with reasons peopleoften give for not investing in professional training.

Sadly, for decades now, I have seen way too many people and organizations give professional training, and certification, short shrift

.Much to their detriment in the end.

This has always baffled me because I have always found value in attending training classes, workshops, seminar, technical conferences, and the like. Even if the class was not great, the contacts I made were always invaluable.I find I learn best working directly with an experienced professional who has “been there and done that”. Or, putting it another way, I like to learn from other people’s mistakes! For me nothing replaces the ability to be interactive and ask questions of a qualified instructor.

The reasons people have given me for NOT taking a training class are basic (i.e., typical):

1. It costs too much (i.e., no budget)

2. I can’t take time away from the daily job (or I can’t afford to have my team out of the office that long)

3. “It’s really not that hard – we can figure it out ourselves reading books and blogs”

Check out how I combat these attitudes by reading the rest of the post at To Train or Not to Train.

Enjoy (and get thee trained!)

Kent

The Data Warrior

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

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