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Archive for the tag “Snowflake Data Cloud”

3 Key Resources for Data Vault on Snowflake

By now you surely know that you can build a Data Vault on Snowflake. In fact we have many customers doing so today. So much so that we formed a Snowflake Data Vault User Group.

Over the years I have had hundreds of calls and meetings with organizations around the world discussing this topic from just basic Data Vault 101 type questions to best practices to who is doing Data Vault on Snowflake. Because of that we developed a Data Vault Resource Kit that points you to all the key blog posts, videos, and customer stories on the topic (scroll down to see everything!). Be sure to bookmark that page. Most of your questions on this topic can be answered there.

To take it a step further and to a deeper level, I partnered up with Snowflake Field CTO Dmytro Yarashneko (CDVP2) and wrote a post with reference architectures and discussions related to doing real time feeds into a Data Vault 2.0 on Snowflake. Check that out here. This article even has code!

And, at long last, for those that want to jump in feet first and try it for yourself, the team built a Data Vault Quickstart , based on the above article and a hands on lab from WWDVC 2021, that gives you a step-by-step guide and all the code to build and load a Data Vault 2.0 system, including an information mart on top of the Data Vault, all in your very own Snowflake account.

So, what is your excuse now? You have all the resources you need to give it a go!

And please, bookmark this post and/or the links above so you don’t lose them!

Model on!

Kent

The Data Warrior

Snowday! Sunny, with a 100% Chance of Innovation

What a great event! So many announcements and great demos, plus and awesome live Q&A with our Snowflake leaders.

At Snowday 2021, Snowflake announced exciting new product capabilities that expand what is possible in the Data Cloud. In addition to announcing Python support in Snowpark (currently in private preview), these latest innovations make it easier for organizations to maintain business continuity across clouds and regions; help data engineers and data scientists build pipelines, ML workflows, and data applications faster; and remove the complexity of getting the right data into the hands of customers.

The Snowflake Data Cloud is a global network connecting organizations through data, creating new opportunities for collaboration to improve business outcomes, and fundamentally changing what is possible across industries. For Kraft Heinz, its data science teams are able to build and test models dramatically faster in Snowflake compared with its prior data lake. For NBCUniversal, it’s building brand-new advertising targeting and measurement products, in a secure and privacy-compliant way using Snowflake’s governance and data sharing capabilities. And for 84.51°, it’s built a Collaborative Cloud that takes complexity off the table and unlocks new possibilities for grocers and CPGs sharing and collaborating on data.

Snowflake continues to expand the scope and possibilities of the Data Cloud, delivering unique innovations that enable customers to:

  • Operate globally
  • Eliminate silos
  • Build faster
  • Create new businesses

Catch up on all the details on the  Snowflake blog.

Check it out!

Kent

The Data Warrior

P.S. Registration for Snowflake Summit 2022 is now open!

 

Snowflake Launches Unstructured Data Support in Public Preview

This is great news that many of us have been waiting for! Now we can have all our data in one place.

From Day 1, Snowflake has supported structured and semi-structured data. Snowflake has provided exceptional performance for those data types and has been a pioneer in processing them. Today, Snowflake is adding support for unstructured data to allow customers to deliver more use cases with a single platform. The support for unstructured data management includes built-in capabilities to store, access, process, manage, govern, and share unstructured data in Snowflake. Now you can get all the benefits of the Snowflake Data Cloud with performance, concurrency, and scale for unstructured data.

Read to entire blog for all the details on how you can use this feature.  Unstructured Data Support in Public Preview

This really opens up a lot of new uses cases and makes doing analytics on unstructured data much easier.

Enjoy y’all!

Kent

The Data Warrior

Snowflake Summit 2021

It’s almost time! The annual Snowflake Summit is just a few weeks away.

Data is everywhere and it holds the keys to unlocking your organization’s success today and in the future. Attend Snowflake Summit and you’ll learn how to use the #DataCloud to unify, analyze, and share data previously out of your reach for more impact than you have ever imagined.

Data Together Now will inspire business and technical leaders, data scientists and engineers, data and analytics professionals, and application developers, to lead their organizations to a data-driven future, today. There is something for everyone in the organization.

You can be a DATA LEADER!

SAVE THE DATE:

AMERICAS: June 8-9  | 9  am PT  |  12 pm ET |  View Agenda

ASIA PACIFIC: June 9-10  | 10 am AEST  |  9 am JST |   View Agenda

EMEA AND INDIA: June 9-10  | 9 am BST  |  10 am CEST  |  1.30 pm IST |  View Agenda

So what are you waiting for? Register today.

Let it snow!

Kent

The Data Warrior

Building a Real-time Data Vault in Snowflake?

Yes you can! The #DataCloud loves #DataVault!

In this day and age, with the ever-increasing availability and volume of data from many types of sources such as IoT, mobile devices, and weblogs, there is a growing need, and yes, demand, to go from batch load processes to streaming or “real-time” (RT) loading of data. Businesses are changing at an alarming rate and are becoming more competitive all the time. Those that can harness the value of their data faster to drive better business outcomes will be the ones to prevail.

One of the benefits of using the Data Vault 2.0 architecture is that it was designed from inception not only to accept data loaded using traditional batch mode (which was the prevailing mode in the early 2000s when Dan introduced Data Vault) but also to easily accept data loading in real or near-realtime (NRT). In the early 2000s, that was a nice-to-have aspect of the approach and meant the methodology was effectively future-proofed from that perspective. Still, few database systems had the capacity to support that kind of requirement. Today, RT or at least NRT loading is almost becoming a mandatory requirement for modern data platforms. Granted, not all loads or use cases need to be NRT, but most forward-thinking organizations need to onboard data for analytics in an NRT manner.

See all the details (and some code) in the full post over on Data Vault Alliance.

Happy Vaulting!

Kent

The Data Warrior

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