Skip to content Professional EditionNEW
Purpose-built environment for small data teams and dbt Core developers. Enterprise Edition is the leading provider of Snowflake environment management, end-to-end orchestration, CI/CD, automated testing & observability, and code management, wrapped in an elegant developer interface.
Spendview for Snowflake FREE

An inexpensive, quick and easy way to build beautiful responsive website pages without coding knowledge.

Pricing and Edition

See whats included in our Professional and Enterprise Editions.

Getting Started
Docs- New to DataOps.liveStart learning by doing. Create your first project and set up your DataOps execution environment.
Join the Community
Join the CommunityFind answers to your DataOps questions, collaborate with your peers, share your knowledge!
#TrueDataOps Podcast
#TrueDataOps PodcastWelcome to the #TrueDataOps podcast with your host Kent Graziano, The Data Warrior!
DataOps AcademyEnroll in the Academy to take advantage of training courses. These courses will help you make the most out of
Resource Hub
On-Demand Resources: eBooks, White Papers, Videos, Webinars

Learning Resources
A collection of resources to support your learning journey.

Customer stories
Connect with fellow professionals, expand your network, and gain knowledge from our esteemed product and industry experts.
#TrueDataOps.Org#TrueDataOps is defined by seven key characteristics or pillars:
Stay informed with the latest insights from the DataOps team and the vibrant DataOps Community through our engaging DataOps blog. Explore updates, news, and valuable content that keep you in the loop about the ever-evolving world of DataOps.
In The News

In The News

Stay up-to-date with the latest developments, press releases, and news.
About Us
About UsFounded in 2020 with a vision to enhance customer insights and value, our company has since developed technologies focused on DataOps.


Join the team today! We're looking for colleagues on our Sales, Marketing, Engineering, Product, and Support teams.
Jevgenijs Jelistratovs - Director of Governance Products & Partner Success, at DataOps.liveOct 25, 2022 3:50:36 PM3 min read

The Road to Collibra Data Citizens '22

The Collibra Data Citizens show in San Diego is only 7 days away now!  In advance of the presentation: Data Products as 1st Class Citizens in a Snowflake Architecture, I wanted to share a prelude of thoughts.

In the early days within the data office, we faced challenges with providing relevant data to our internal or external customer. There are various areas to focus on why that was, but as one Head of Data Office recently asked me, “What would you start with if you had a blank slate?” I said, “governance of course, but I'm biased.” He told me that “while many enterprise governance initiatives have been less successful than hoped, he'd start with it too!” The real question is why is there that perception?  

From my experience, data governance is not only about the defensive aspects of working with data, like defining standards and policies, but also business critical needs like connecting your data producers to data consumers. Working with organizations to help setup a data governance office, I've been faced with a lot of cases where we wanted to speed up the delivery of data "products" to the consumer. In these early days we never called the deliverables “data products”, but we did place value on them and treat them as "sellable" items to an internal (in most cases) consumer.  

Defining those sellable items in Collibra we'd often confuse ourselves a little bit as we didn’t have a standard to clearly differentiate between the Table or Data Set being that consumable piece. "Why can't we use a Snowflake/BQ table, instead of using a Data Set in the shopping for data process?" was a frequent question. I'm sure a lot of practitioners would face similar questions in previous days defining data products, thinking of it just a Data Set (term being standardized now), or let's say a Tableau Report. (BTW, as you already likely know, Collibra has now added Reports as a Standard Asset Type supported by the shopping for data process) The key thing we have learned is that it is critical to work closely with your Data Consumer and their business requirements for the data insights.


Table Level
access is quite straight forward and understandable in many instances where we would want to manage access control for example. But if we want to provide an atomic sellable piece to the end user, we might require the ability to know who "bought" that piece of data, and to check the contract (or data sharing agreement) on how and by whom it can be used, ensure data quality and freshness, and allow consumption of our precious data though multiple channels—in these instances we might find the Data Set concept useful, if sometimes not enough…  

Today, we are now simply evolving past that, and have started to define an agreement in our organizations on what that “consumable” piece of information is and define a common understanding of that for all to know. In this context I believe, is where the Data Product concept is truly being born. A Data Product becomes a mix of structural components, supporting process and organization. When we look at the implementation of data products at scale, the automation of both governance processes of consumption of each data product, and the data engineering layer where the Data Product is been produced is critical, to ensure Data Product adoption and usability.  


In our session at Collibra DC2022, we are going to have a closer look into the operating model and definition of the data products in Collibra &, plus future opportunities for DQ & Observability, and lessons learned.  Come and join us