Data Governance Training: Why It’s Critical to Adoption

Updated November 19th, 2024

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Do you need data governance training? The short answer is yes!

When it comes to data, the data is clear: 65% of leaders say that governance is a top priority for their organization. That’s because good governance produces business value in the form of high-quality, discoverable, governed, and secure data that drives business results.
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But here’s the catch: Good data governance only happens when everyone in your organization actively participates. However, without proper training, your program will likely fail to catch on.

Here’s why data governance training is so important to getting (and keeping) your people on board, what it should cover, and some of our recommended best practices for running a data governance training program.

Table of Contents #

  1. Why do you need a data governance training program?
  2. Basics of data governance training
  3. How to conduct data governance training
  4. Best practices for data governance training
  5. Conclusion
  6. Related reads

Why do you need a data governance training program? #

Too many companies treat data governance as a “one and done” initiative, putting a program in place and then wondering why people don’t seem to engage with it. Full data governance adoption starts with training, and proper training is an ongoing investment.

A very worthwhile investment, though, because it delivers business value in three key ways:

  • Improves data governance adoption
  • Codifies a standardized approach to data governance
  • Breaks down resistance to governance procedures

Let’s look at each of these in detail.

Training improves data governance adoption #


“If you build it, they will come.”

Well, that might be true for a magical baseball field but, tragically, not for data governance. When you first implement a governance program, many people in your org will be unfamiliar with data governance and why it’s important. To them, it might just sound like more busy work.

Formal training gets people on board by showing how data governance policies create high-quality and secure data. It helps them understand the deep connection between data governance and business value. Most of all, they learn how good governance leads to:

  • Improved decision-making
  • Increased efficiency
  • Fewer data breaches
  • Increased revenue
  • And many other benefits

Data governance training also teaches employees how to use your org’s data governance tools to benefit their most important work.

Training codifies a standardized approach to data governance #


Without formal training on the right way to run data governance, groups have to DIY it through informal training (there are an astonishing number of data governance YouTube videos), hand-me-down knowledge, or even trial and error. This can cause two problems:

  • A knowledge gap, as experienced members who knew the policies and procedures leave and new ones who aren’t as familiar with the lore replace them; and
  • Different teams following divergent data governance practices.

Standardized training ensures new hires understand your data governance procedures from day one, and it also reinforces understanding among current employees. The result is consistency across teams and smooth handoffs when roles change.

Training breaks down resistance to governance procedures #


Traditional data governance was often a top-down, heavily bureaucratic affair. Gartner estimates that the lack of flexibility with this approach dooms around 80% of these programs to failure. Users who’ve experienced this traditional approach may regard “data governance” as a dirty word.

Fortunately, modern data governance is much more flexible. Architectural advances like data mesh have emerged to combine local control with centralized oversight, making it possible to have rapid data product development without sacrificing compliance.

Governance training, though, can dispel any negative perceptions by showing users how modern data governance focuses on speeding up work — not slowing it down.

Basics of data governance training #

What should you cover in data governance training? At a minimum, you should hit the following fundamentals:

  • Data governance policies
  • Data quality standards
  • Security
  • Compliance and classification
  • Data governance processes and tools

Data governance policies #


A data governance policy outlines your company’s “rules of engagement” for data, including how it’s accessed and processed. It covers compliance with both internal rules and any applicable regulatory standards.

In modern data governance, some — maybe even most — of your data governance policies will be enforced through automation. Even so, users need to know what these rules are so they know how to respond when data quality or data compliance-related notifications pop up.

Data quality standards #


Data quality is the primary goal of data governance because quality directly impacts data’s usability and business impact. Training should emphasize the crucial role data governance plays in providing everyone with better data for decision-making. It should also cover key data quality concepts like using data lineage to document and build trust in data.

Security #


Data breaches cost companies an average of USD 4.88M per incident. Beyond financial loss, breaches can damage a company’s reputation in ways that are hard to come back from. Data governance training should cover how to secure data using role-based access controls (RBAC), as well as best practices for managing access to sensitive information.

Compliance and classification #


Data compliance — ensuring that sensitive data is protected according to industry standards and governmental regulations — can also have a drastic impact on the bottom line. Consider the case of Meta’s €1.2B fine for failing to comply with GDPR requirements.

Compliance training should cover data sensitivity classification procedures, classification levels, and how to monitor compliance at both team and organizational levels.

Data governance processes and tools #


Finally, your data governance training program should address all the processes and tools used in day-to-day data governance work. This includes tools for any of the processes above as well as any tools or processes that may be specific to certain roles or teams.

Ideally, this part of the training program should have interactive elements so users can get hands-on, direct experience with the tools in a safe environment before using them in the real world.

How to conduct data governance training #

Now you know what needs to be in a data governance training program. But how do you go about conducting the program itself? Options include one or a mix of the following:

In-person training: Classroom training can encourage more camaraderie and sharing of insights and experiences. A major benefit is also that users can ask experts pointed questions and receive real-time answers. The downside is that live training sessions can be time-consuming and expensive to support. In-person training also limits who can attend and how many times you can run it.

Virtual live sessions: Virtual live sessions are cheaper to offer and have many of the same benefits as in-person training. Like in-person training, however, you’re limited in how often you can offer them.

Virtual self-paced sessions: Pre-recorded, interactive training modules on a Learning Management System (LMS) are the most flexible option. They don’t require a live trainer, they scale more easily, and employees can take them at their own pace. The downside is that users lose some of the benefits of being face-to-face with experts.

Whatever modality you choose, all data governance training should support:

  • A mix of conceptual instruction and hands-on learning
  • A way for users to ask questions, whether to experts or the larger community (e.g., a discussion forum)
  • Quizzes and assessments to verify knowledge learned
  • Tools to track who’s completed the training

Best practices for data governance training #

Want to get the most out of your program? Here are some best practices we’ve seen from our customers (or implemented ourselves):

Adjust training for each role. Data stewards will need different training than data engineers, who will, in turn, need different training from business users.

  • Both data engineers and stewards will need training on root cause analysis of data issues
  • Data engineers will need training on building data pipelines and interfacing with various data governance systems via APIs
  • Business users will be most concerned with using a data catalog and data lineage to find, vet, and utilize data

Tailoring the training to fit your company’s different personas will maximize your program’s engagement and effectiveness.

Track training centrally for compliance. Use an LMS to track and report on who’s taken the training and who’s due for a refresher.

Keep training up to date. Training isn’t a one-off project; it’s a living asset that must evolve as your governance program matures. Revise your training as you refine your tooling and data governance procedures.

Leverage external training. Third-party training packages and vendor-specific tooling training programs can decrease the custom training you need to create and maintain.

Choose data governance tools that are easy to use. Training will be easier if you deploy tools — data catalogs, classification engines, data lineage graphs, etc. — that are intuitive for users of any technical level.

Conclusion #

Training can happen in person, live virtual sessions, or self-paced online modules. However, no matter the setting, it should be role-specific, centrally tracked, and regularly updated.

For best results, start thinking about data governance training as you’re building out your data governance architecture. Choosing tools that are well-documented and easy to use will encourage adoption and make training a lighter lift.

Atlan provides AI-powered modern data governance with an intuitive user interface that any data stakeholder can use. Any user can leverage Atlan to define data governance policy workflows, manage policy exceptions, classify and document data, and perform self-service data discovery.

Learn more about Atlan’s data governance capabilities - book a demo today.

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