Guide to Agile Data Governance

Even with executive and stakeholder buy-in, Data Governance can be seen as too big a lift and might be deprioritized in favor of initiatives with more immediate ROI.

In this guide, we'll look at how organizations can utilize the iterative, collaborative approaches that might already be in place for product development and project management for more effective and transparent Data Governance initiatives.

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What's in Your Guide

Data Governance should be at the heart of every decision involving your data estate. For that to happen, Data Governance shouldn’t be viewed as a heavy lift – but as an integrated, strategic component of data management.

With a focus on Data Governance, you can unlock the ROI potential of organizational data by enabling employees to best know, trust, and use data in scale to drive revenue and efficiencies.

In this Guide, we explore how to introduce the concept of Agile Data Governance into your organization and provide challenger questions to help identify a first use case.


Guide Chapters

Data Governance Primer

To understand Agile Data Governance, it’s important to define what Data Governance is - and what it is not. Explore Data Governance principles that support security AND accessibility in your organization, and identify key strategies to developing a Data Governance posture.

Agile Data Governance

Can Data Governance be Agile? Learn how to use the the iterative, collaborative approach of Agile Methodology to implement more effective and transparent Data Governance initiatives.

Find Your First Use Case

Ready to get started? We’ve posed five questions that can help you find the first use case for Agile Data Governance in your organization, whether it’s building off of successes in your team, establishing a data dictionary, or identifying easy first wins.

Building an Agile Data Governance Toolkit

There is no tool that can provide a cure-all for Data Governance, but finding the right technology to support your journey will help you automate critical processes and build Data Governance into data management throughout the data lifecycle.

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