Data Governance and the Snowflake Cloud Data Platform — Unlock Your Potential

Organizations are looking to drive agility and maximize the potential of their analytics initiatives by building new systems or modernizing consolidating existing on-premises systems in the cloud. With its unique architecture, Snowflake Cloud Data Platform provides elasticity, native support for diverse data, and compelling performance at a fraction of the cost while eliminating the complexity of conventional data warehouses. However, you need a way to identify and bring all that data into Snowflake, and then manage and govern it in a way that can run on any cloud for all workloads. The success of your data warehouse and data lake modernization initiatives depends on having trusted, high-quality data – and that means having a data governance program in place.

What is data governance for data warehouses? Why is it important?

Data governance is a collaboration between IT and the business, who must consistently and collaboratively improve the trustworthiness and quality of their data to power key business initiatives and ensure regulatory compliance.

It’s important because – while migrating to the cloud data warehouse or data lake, you don’t want to move incorrect and untrustworthy data. Doing so will have serious implications on your business. Significant risks of inadequate data governance for your data warehouse or your data lake include:

  1. Poor data governance can impact regulatory compliance activities
  2. Unreliable data will have both short term and long-term influence on business decision making
  3. Inability to experiment new things quickly.

Making the most of Snowflake’s Cloud Data Platform with data governance

There are many advantages of moving data into Snowflake’s Cloud Data Platform. The obvious ones are – cost and flexibility. But if you move bad data then you will end up making bad decisions. (Listen to Susan Wilson, VP of Data Governance and Privacy, Segment Leader, at Informatica, on The Importance of Data Quality and Data Governance in the Snowflake Data Cloud.)

To reap the full benefits of Snowflake’s cloud data platform:

  1. You must eliminate data silos inside and outside of the organization.
  2. You need to know what your data is and how it is being used.
  3. You need have a flexible approach to manage risk.

In order for the Snowflake Data Cloud ecosystem to be successful for customers, partners, data providers, data service providers to gain access to data sets in a secure, governed, compliant and seamless way, a robust democratization platform is needed to ensure all roles can engage, that definitions and rules are operationalized.  

Leading organizations rely on Informatica for end-to-end data governance due to a deep breadth of capabilities. Informatica’s modern, AI-driven cloud-native data platform offers the only truly integrated, intelligent and automated solution to governance and data democratization.

Informatica is committed and heavily investing its resources in its Snowflake partnership to make sure that organizations have access to extensive platform capabilities for successful Snowflake projects.  

Data democratization, Snowflake, Informatica, and you

Snowflake Cloud Data Platform can form an integral part of data democratization initiatives. Take a closer look at the attributes that make up the data democratization platform.

AI-Driven Metadata Management Foundation | Informatica

With the unified data cloud architecture powered by Informatica and Snowflake, organizations can easily transform, integrate, and analyze all of their data. They can also securely share, acquire, or even monetize live, governed data, as well as build and operate their data applications. It scales instantly and near-infinitely. It enables any organization to operate across different infrastructure cloud providers and their regions as a single cloud, while satisfying industry and regional data privacy requirements.

Next steps

Over the last few years, we have seen that the customers that are the most successful at becoming data-driven in fact start by asking themselves a fundamental question: How do I decide what data to move first? You want to make sure that you start with those use cases that will yield the most value, quicker.  Start small but have a long-term strategy in place.

Secondly you do need to make sure that you have a robust, scalable mechanism to move data into Snowflake reliably with the help of extensive data governance system.