What Is Data Governance? Data Governance 101

Learn more about data governance—the practice of creating policies, procedures, and standards to manage and protect data across an organization.

Best Practices
June 21, 2023
Image of Noorisingh Saini
Noorisingh Saini
Content Marketing Manager, Amplitude
What is data governance - blog post's featured image illustration

The average cost of a data breach globally is $4.35 million. Proper data governance protects your organization’s most important asset—digital information—from the consequences of data breaches and disruption.

Data governance is the practice of creating policies, procedures, and standards to manage and protect data across an organization. Every organization, regardless of size and industry, can benefit from a comprehensive data governance plan.

Here’s how a data governance strategy—and the right data governance tools—can help you protect your organization.

Key takeaways
  • Data governance is the process of controlling and protecting your organization’s data throughout the data lifecycle—both to secure your data and to ensure better business outcomes.
  • Organizations achieve better data stewardship by combining data policies, processes, data governance tools, and regulatory standards.
  • Effective data governance is important to everyone, especially for those operating with sensitive data (such as HIPAA data).
  • Without proper data governance, an organization could find itself experiencing a serious data breach, disruptive data loss, and misleading data analytics.

What is data governance?

Data governance is a set of practices that help ensure the safe and effective use of data. It also helps your organization maintain data quality, which is critical for informed decision-making.

Major components of data governance

Because data governance is complex, it can be helpful to break it down into its major components. Data governance consists of several pillars that organizations must address to ensure data security and integrity.

  1. Policies: One of the first steps in implementing a data governance framework should be establishing policies for the collection, storage, use, and transfer of data. Data assets must be protected both at rest (while being stored) and in motion (while being transferred).
  2. Procedures: An organization must establish procedures to ensure the proper handling of data in compliance with its policies. An organization’s policies won’t be effective if they aren’t being followed—and an organization may not know that they aren’t being followed unless it builds checks and balances within its procedures.
  3. Standards: Standards ensure the organization manages data consistently. Standards govern the baseline at which the organization must protect its data; a regulatory body often sets these standards based on industry and data type.
  4. Tools: Data governance tools enforce these policies, procedures, and standards. An organization can manage and maintain its data governance more efficiently with tools. Amplitude is SOC 2 Type 2- and ISO 27001-certified, ensuring security, confidentiality, and availability for our customers.

Together, these four pillars form a complete data governance strategy. Every organization’s data governance strategy will be unique, however, because every organization deals with different types of data—whether it’s a healthcare organization dealing with Sensitive Personally Identifiable Information (SPII) or an education app dealing only with customer-furnished Personally Identifiable Information (PII).

The importance of data governance

Poor data governance can lead to security breaches or disruptive data loss, which can have devastating consequences for businesses—including costly penalties and loss of customer faith. Data governance is closely related to data security, as data governance is what enables data security policies to remain effective.

Data governance helps your organization:

  • Ensure compliance with laws and regulations surrounding data
  • Increase the quality of data used to make data-driven decisions, such as product data management
  • Prevent costly data breaches and data loss by keeping data protection standards up to date

But organizations aren’t just dodging fines and penalties with a data governance strategy. They’re protecting the data most valuable to their business.

Data governance can help an organization by:

  • Taking a more systematic approach to collecting, organizing, and analyzing data, thereby making better decisions rooted in reliable information
  • Reducing costs by streamlining processes and improving efficiency and productivity metrics
  • Building customer trust, confidence, and satisfaction by ensuring that the organization handles its customer data securely and responsibly

Implementing a data governance strategy

Implementing a successful data governance strategy requires careful planning, collaboration, and execution—in addition to the right tools.

Best practices for successful data governance

The following best practices make it easier for organizations to create efficient, secure data governance strategies.

  • Establishing roles and responsibilities: Establishing roles and responsibilities will restrict data to those who need it. Clearly define the roles and responsibilities of those involved in managing data with least-privilege access or even zero trust. Meanwhile, elect data stewards and identify key stakeholders to ensure that action is taken if a threat does occur.
  • Training: Training employees on data governance policies and procedures is essential for maintaining compliance. Data breaches often occur when people make mistakes—and anyone can make a mistake. But training will help your team build better overall data governance, protection, and security habits.
  • Auditing: Regularly auditing the system helps identify potential data risks and ensures that the company follows the data governance framework. Over time, data security and governance can drift. Proper auditing reduces this drift and helps the organization adapt to shifting needs.
  • Monitoring: Routinely monitoring data usage helps organizations quickly identify suspicious or unauthorized activities. Today, advanced monitoring systems driven by AI technology can identify suspicious activity, even internal.

Challenges to data governance

The rapid growth of data and technology has presented modern challenges to traditional data governance in terms of both data volume and regulation.

  • Data volume: As organizations generate more and more data, it can be difficult to keep track of all the data elements, where they are stored, and how companies use them.
  • Regulation: With new technologies such as machine learning and artificial intelligence emerging, organizations must ensure that they govern these technologies properly—regulations still haven’t quite caught up, and when they do, organizations will have to adapt.

Organizations must be prepared to compile ever-larger data sets using the tools available to them—and they must be cautious to ensure that the tools they use are secure and compliant.

The risks of poor data governance

Poor data governance can lead to revenue loss in a number of ways.

  • Data compromise: A confidential or sensitive information leak can lead to financial and reputational damage.
  • Financial loss: Businesses may be forced to pay ransomware threats, lose time to manual data recovery, or lose business during the time it takes to recover their systems.
  • Legal risks: Organizations could face legal action if they fail to comply with constantly changing laws and regulations governing the use of personal data.
  • Customer loss: If you’re irresponsible with your customer’s sensitive data, you’ll lose their trust and business.
  • Poor decision-making: If your data isn’t correct, your business decisions won’t be, either. This is especially true for complex enterprise data, which could potentially be very misleading if data integrity isn’t maintained.

Data governance into the future

As data security concerns grow, the need for strong data governance policies and processes will only become more important; however, the nature of data may also change. Preparing for data governance in the future means investing in tools and partnerships that will adapt to evolving technologies and regulations.

New regulations for data governance

Governments and regulatory bodies worldwide are introducing new regulations to ensure that businesses comply with data protection laws. Some examples include:

  • General Data Protection Regulation (GDPR): The GDPR is a set of European Union regulations designed to protect the personal data of EU citizens. Other countries are now looking at this as an example.
  • California Consumer Privacy Act (CCPA): The CCPA is a California law that gives consumers more control over how businesses use their personal information. Other states may follow with similar regulations regarding data catalogs.

Because AI technology is becoming more advanced and readily available, new regulations are likely to emerge regarding how AI/ML can utilize collected data. Anyone using AI/ML for their organization (from marketing to analytics) must consider this.

Tools and technologies for managing data governance

Data governance is complex and changing all the time. But organizations can leverage new tools and technologies to stay compliant and improve their data governance. Some notable data stewardship tools include:

  • Machine learning (ML): Machine learning can help to automate the process of monitoring data and flagging suspicious activities while also digging deeper into the meaning behind the data collected.
  • Automation: Automating certain processes, such as setting up access controls and tracking changes, can help organizations save time while improving accuracy and security.
  • Analytics: With analytics tools, businesses can monitor their data usage in real-time and gain valuable insights into their data usage. From there, they can optimize even big data and improve their business intelligence strategies and data governance processes.
  • Data governance platforms: A comprehensive data governance platform can help your business follow data governance best practices and manage data more efficiently while ensuring regulatory compliance.

Build data governance into your data strategy

As data becomes an increasingly important asset, building data governance into your organization’s strategy is essential. Amplitude can help your data governance initiatives.

With Amplitude Analytics, you can:

  • Govern your data sources and data modeling in one all-in-one, out-of-the-box solution.
  • Restrict data access to your data to only those who need it.
  • Use machine learning and at-a-glance insights to get actionable information.

At Amplitude, we take data security seriously—to take the burden off of you. Rather than worrying about data standards and data storage, you can concentrate on the benefits of data analytics and digital transformation. Sign up for free to get started on your data governance journey.

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About the Author
Image of Noorisingh Saini
Noorisingh Saini
Content Marketing Manager, Amplitude
Noorisingh Saini is a data-driven Content Marketing Manager and Amplitude power user. Previously, she managed all customer identity content at Okta. Noorisingh graduated from Yale University with a degree in Cognitive Science, specializing in Emotions, Consumer Behavior, and Behavioral Decision Making. In her free time, she runs a personal blog with over 50K+ followers.

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