The Data Warrior

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Archive for the category “Data Modeling”

WWDVC 2022 is almost here – Are you ready to “up” your Data Vault game?

Vermont is beautiful in May!

As the world is coming out of its pandemic induced isolation, its time we all got back to meetin’ and greetin’ our colleagues and peers in person. One of the things the last two years has taught us it that humans are social animals. We like being around other humans and some variety is good for our mental and emotional health (not that we don’t all love the families that we have been locked up with during this time). Not only that, but we learn and communicate better face to face. So much of our communication is nonverbal and just can’t be seen behind a mask, or a Zoom square.

Are you ready to get back out there, network with your peers, meet some Data Vault Masters, and work on your professional development around Data Vault? If you are then it is time to secure your seat at the 2022 World Wide Data Vault Consortium (WWDVC). As in past years, it will be held near the end of May at the lovely, and family friendly, Stoweflake Lodge in Stowe, Vermont.

Check out all the details, including HOLs, keynotes, and session topics, about WWDVC 2022 in this post by Cindi at DataRebels WWDVC 2022 is almost here

If you are already planning to go, you can just register here.

Keep on modeling!

Kent

The Data Warrior

Tips for Optimizing the #DataVault Architecture on Snowflake (Part 3) 

For this last post in my current Data Vault (DV) series, I will discuss two more cool features of Snowflake Cloud Data Platform (@Snowflakedb) that you can take advantage of when building a DV on our platform. If you are not familiar with the DV method, please read my introductory blog post and part 1 of this series before reading this post.

Get the details here: Tips for Optimizing the Data Vault Architecture on Snowflake (Part 3)

Happy Data Vaulting!

Kent

The Data Warrior

Tips for Optimizing the #DataVault Architecture on #Snowflake (Part 2)

SETTING UP FOR MAXIMAL PARALLEL LOADING!

In this post, I discuss how to engineer your Data Vault load in Snowflake Cloud Data Platform for maximum speed.

Because Snowflake separates compute from storage and allows the definition of multiple independent compute clusters, it provides some truly unique opportunities to configure virtual warehouses to support optimal throughput of DV loads.

Along with using larger “T-shirt size” warehouses to increase throughput, using multi-cluster warehouses during data loading increases concurrency for even faster loads at scale.

Get the details –  Tips for Optimizing the Data Vault Architecture on Snowflake (Part 2)

Enjoy!

Kent

The Data Warrior & Chief Technical Evangelist for Snowflake

Tips for Optimizing the #DataVault Architecture on #Snowflake

Data Vault is an architectural approach that includes a specific data model design pattern and methodology developed specifically to support a modern, agile approach to building an enterprise data warehouse and analytics repository.

Typical Data Vault Design with Hubs, Sats, and a Link

Snowflake Cloud Data Platform was built to be design pattern agnostic. That means you can use it with equal efficiency 3NF models, dimensional (star) schemas, DV, or any hybrid you might have.Snowflake supports DV designs and handles several DV design variations very well with excellent performance.

This series of blog posts will present some tips and recommendations that have evolved over the last few years for implementing a DV-style warehouse in Snowflake.

Here is the first set of tips:Tips for Optimizing the Data Vault Architecture on Snowflake (part 1)

I hope you find this helpful!

Kent

The Data Warrior and Chief Technical Evangelist for Snowflake

Better Data Modeling: Agile Data Engineering

You asked for it, you got it!

Ever since I wrote my Kindle book on Agile Data Engineering and Data Vault 2.0, many, many people have asked me to provide it in a hardcopy format. Well, I finally managed to find time to convert that ebook into a paperback book (I even corrected a few errors in the process).

If you forgot what the book was about, here is the description:

This book will give you a short introduction to Agile Data Engineering for Data Warehousing and Data Vault 2.0. I will explain why you should be trying to become Agile, some of the history and rationale for Data Vault 2.0, and then show you the basics for how to build a data warehouse model using the Data Vault 2.0 standards.In addition, I will cover some details about the Business Data Vault (what it is) and then how to build a virtual Information Mart off your Data Vault and Business Vault using the Data Vault 2.0 architecture.So if you want to start learning about Agile Data Engineering with Data Vault 2.0, this book is for you.

So here it is – Introduction to Agile Data Engineering – now available to purchase on Amazon.

Get your copy now. Next time you see me at an event, I will be happy to sign it for you. 🙂

Enjoy!

Kent

The Data Warrior

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