Since organizations first started using data, the need to govern it has never let up. While governance means different things to different people and different teams, one thing is certain: The long sought-after panacea for data governance remains elusive, and organizations continue to exert a great deal of time and effort trying to figure out how to effectively govern their critical data assets. 

The Changing Landscape of Data Governance

The technology industry has taken great strides to help. According to Business Wire, by some estimates, the technology side of data governance has led to a strong and vibrant segment of the broader data management market and at over 20% growth projected, it’s showing no signs of slowing down.1 Today, Snowflake partners with several vendors that are leading the charge in helping solve a range of data governance challenges.

Collibra, for example, develops solutions focused on governance and stewardship with the end goal of giving all data users the benefits of having easy access to good and trustworthy data.2 Another partner,, delivers a data catalog that maps siloed, distributed data to familiar and consistent business concepts, so users can get clear, accurate, fast answers to business questions.3

Investing in Data Governance Capabilities

Snowflake has a strong focus on data governance capabilities to help our customers better manage their data. For example, row access policies (now generally available) enable enterprises to secure data using fine-grained, content-based access control. Column-level security (now generally available) enables a masking policy to be applied to a column within a table or view for control over sensitive data. Combined with external tokenization, this can be further enhanced by third-party tools such as Protegrity4 or Micro Focus Voltage.5 And our recently announced Object Tagging feature (currently in public preview) helps users better know and organize their data by allowing them to attach user-defined metadata to a variety of objects, including tables, views, and columns.

Where things get really interesting for Snowflake and data governance, however, is the Data Cloud. While each of the features and technologies discussed to this point play a very important role in solving governance challenges, one key problem remains unaddressed: the data silo.

Breaking Down the Walls Created by Data Silos

For a few reasons, data silos are arguably the Achilles heel of any data governance initiative. First, silos typically exist to meet the needs of different stakeholders. This means there are different requirements for how data is collected and consumed and that may require multiple, different governance processes. More silos leads to more governance policies, which leads to extra time and overhead to keep things under control. Maintaining trust relationships across silos is difficult. 

Second, silos have many shapes and sizes. A silo can be a database, a file, or a spreadsheet. As silos grow in numbers, tracking where data is going (and how) becomes a daunting task. Ensuring that the data-consuming parties are handling data in the agreed-upon way often takes a lot of faith. And third, tracking data over its lifecycle is complicated and prone to risk. Keeping track of how data is moving and morphing becomes increasingly complex the more silos data spans. 

The Data Cloud changes this by breaking down silos in new ways. In the Data Cloud, data can be connected and teams can collaborate across common data sets, regardless of whether they are in the same team, department, or organization. Because data is inherently connected in the Data Cloud, governance policies are easier to apply across disparate needs, and in a centralized way. 

For example, data masked in a table created by company A means only those users with specific roles are able to see data in its full fidelity. If company A shares that same data with company B, those same policies can be made to apply to the share. There’s no silo to manage and no need to create another masking policy. Data governance is made easier by connecting data in ways it has not been connected before. Lineage and traceability across the ecosystem benefit in the same way. 

Combined with the connected nature of the Data Cloud, the core governance capabilities in Snowflake and the ecosystem of governance partners can finally help organizations get a leg up on data governance.