Just a quick note – I just found out SqlDBM has featured me on their new advisors page. Check it out.
Also wanted to remind everyone that I will be giving a webinar next week, August 17th on Data Modeling for Snowflake, Sign up here for that. It will be fun for sure.
Ciao for now!
Kent
The Data Warrior
A few weeks back, right after attending Snowflake Summit, I had the pleasure of chatting with Sanjeev Mohan on his podcast – It Depends. We spent an hour or so chatting about trends in modern data management, data mesh, data vault, my now semi-retired life as an advisor to several Snowflake partners, and my love of martial arts.
So sit back, relax (I did), and enjoy!
Aloha.
Kent
The Data Warrior
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
Back in the saddle again for The Data Warrior! Here is a piece I just did for the folks at Wherescape about one of my favorite topics – Automation!
The world of data has changed for sure. Especially over the past several years. In fact, the pandemic accelerated some changes, like the migration to cloud-based data platforms. When everyone needed to be remote, it just made sense to move to the cloud and use a service for your data platform.
Along with that came more data, more data types, and an actual business needs to move faster. Companies had to adapt very quickly during the pandemic if they wanted to survive. Many did and thrived while others, well, not so much.
As the demand for data continues to grow at unprecedented rates, and as it becomes a non-negotiable asset for organizational success, the requirement to rapidly deliver value from that data (i.e., turn it into information for data-driven decision making) has become an imperative.
So how do we deliver value faster with our data warehouses, data meshes, and enterprise data hubs? Automate, automate, automate.
Check out the full post here – Why Automation is No Longer a Choice for Your Data Architecture
Enjoy!
Kent
The Data Warrior
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
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