The path to comprehensive data governance for Google Workspace users

For modern organizations, data represents a crucial facet of business intelligence and strategic decision-making. But as the volume of data held by virtually every organization scales exponentially, effective handling and protection of that data becomes more important than ever. Enter: data governance.

What is data governance?

In simple terms, data governance is the set of internal policies regarding the way data is collected, stored, handled, and disposed of within a given organization. Data governance dictates what happens to data throughout its entire lifecycle, from collection to disposal.  

More formally, the Data Governance Institute (DGI) positions it this way: “Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”

Core principles of data governance

Data governance can mean different things to different organizations. But at its core, the concept of data governance involves eight essential principles:  

1. Integrity: Those who participate in data governance processes must practice integrity and honesty when discussing matters involving data.

2. Transparency: It should be clear how and when data processes were introduced, to all participants involved.

3. Auditability: Data governance should be auditable, especially for compliance and operations auditing requirements; documentation should be created and retained to support compliance and audit requirements.  

4. Accountability: Your data governance policy must define who is accountable for cross-functional data processes and controls.  

5. Stewardship: Define responsibilities for people and groups who are accountable for data.

6. Checks-and-balances: Data governance accountabilities must ensure there is a checks-and-balances system in place among those who collect, manage, or use data.

7. Standardization: Introduce and support the standardization of an organization's data across the business.  

8. Change Management: Implement a system for controlling how data changes, with regard to both proactive and reaction processes.  

While the real-world benefits of an effective data governance program are significant and wide-ranging, there are also seven universal key objectives for data governance programs:  

1. Enable better decision-making

2. Reduce operational friction

3. Protect the needs of data stakeholders

4. Train management and staff to adopt common approaches to data issues

5. Build standard, repeatable processes

6. Reduce costs and increase effectiveness through coordination of efforts
7. Ensure transparency of processes  

In the simplest terms, data governance brings consistency, risk mitigation, a single source of truth, cost savings, and visibility into your data estate and its operations.

Assessing your current data governance maturity

But of course – not all data governance programs are created equally. No matter the size of your organization, it’s crucial to examine your data governance to determine its effectiveness and identify weaknesses and opportunities.  

Rather than waiting for planned changes to take effect – or putting it off altogether – it’s important that organizations assess the maturity of their data governance programs now, rather than later.  

Data governance maturity models are used to help organizations gain this understanding. These maturity models are designed to help organizations evaluate and communicate the current state of their data governance program. Maturity models should be used on an ongoing basis to ensure organizations can track improvements and growth in their data governance program, as well as proactively identify aspects that might have fallen through the cracks.  

The RecordPoint team has extensive expertise in data governance, and are here to assist organizations conduct these assessments. By utilizing their deep knowledge and experience, the RecordPoint team can provide valuable insights and guidance to help organizations understand their current maturity level and identify areas for improvement.

Establishing a data governance framework

Setting up a data governance framework from scratch might seem intimidating, but it doesn’t have to be. While your organization’s program must take into account the distinct needs and circumstances of the business, the process of setting up a data governance framework involves these specific steps:

1. Define the goals and objectives of your data governance program, considering both long- and short-term goals, as well as the implications of factors like relevant privacy regulations.  

2. Secure executive and key stakeholder buy-in, to ensure program participation and drive a data-aware culture in your organization.  

3. Ideate, assess, and build data governance practices, mapping out the people, processes and technology required involved for each step of the data lifecycle.  

4. Define clear roles and responsibilities of people and groups accountable for executing data governance processes; include anyone involved with the collection, storage, handling, security, or disposal of data.

5. Document your organization’s data governance processes, ensuring your policies are easily accessible and understandable to everyone involved.  

6. Iterate and optimize your data governance framework, using maturity models, data insights, and feedback from program participants.  

Implementing data management practices for Google Workspace

While Google Workspace is becoming the platform of choice for many enterprise organizations around the world, thanks in part to its strong collaboration and customization capabilities, complex data management needs may not be met byt the platform. While Google Workspace users do have access to Google Vault, it doesn’t provide the fined-tuned data control required by highly-regulated organizations.  

Limitations to data management with Google Workspace

There are a few different ways in which Google Workspace’s data management capabilities may fall short of what an organization needs to maintain data visibility and regulatory compliance.  

• Limited to Google Workspace data: While Google Vault can handle data within your Google Workspace instance, it’s not capable of managing data created or stored in other systems or data sources. For example, data that exists only in systems used by sales, finance, or other departments (think Salesforce or Workday) cannot be managed in Google Vault. To gain a comprehensive understanding of your data security posture, you need to full visibility into your entire data estate – not just your Google data.

• Retention management constraints: When managing data in Google Vault, limited metadata is stored, and there are narrow limits on how retention rules and triggers can be set. Retention periods can be based on a small number of options, including Date created, Date moved to bin, or Date set on label data. In addition, retention periods are set on a per-application basis, meaning only one rule can be set for each application, like Gmail or Google Drive. Because of these constraints, custom retention policies are restricted, and may not provide the flexibility organizations need to meet their regulatory requirements.

• Basic search and export functionality: While Google Vault does provide search and export functionalities, they are limited in comparison to the more advanced eDiscovery tools on the market, which are more likely to provide the comprehensive search and export capabilities you need to operate with compliance confidence.  

• Limitations to legal holds: When specific information needs to be retained for legal holds or audit processes, Google Vault instead places specific accounts or groups of people on hold, which is unlikely to work as a scalable solution.  

The RecordPoint solution

Our platform was designed to ensure you have full visibility and control over your data over its entire lifecycle. See how features like these can help your company remain compliant with its regulatory obligations.  

• Data inventory - Gain a comprehensive view of your data estate, including both data within your Google Workspace instance and outside it. Use our simple Connectors to integrate with all your essential business systems to create and maintain a dynamic data inventory that ensures you know that what, how, and where of all the information you hold.  

• Data lifecycle intelligence - Infuse intelligence throughout the data lifecycle, using AI and machine learning to instantly identify sensitive data, then manage and dispose of data according to your unique policies.

• End-to-end governance - Mitigate risk with end-to-end governance policies that work across your data estate, including Google Workspace data and beyond. Leverage AI-powered compliance controls to implement and optimize your data governance processes, including retention, classification, all the way through to defensible disposal.  

• Platform security – Protect sensitive information, no matter where it lives, with PII and PCI data intelligence, giving you a clear view of how constantly-evolving cyber threats may affect your organization and its data.  

Ensuring data privacy, compliance and security

Ultimately, the most crucial aspects of data management are the maintenance of data privacy, regulatory compliance, and organizational security.  

For highly-regulated organizations, there is no room for error in complying with regulations like the GDPR or CCPA, which carry stiff penalties that can cost businesses up to 4% of their annual global turnover, or up to €20 million, and may be even higher in the case of CCPA violations.  

While no organization can make themselves totally impenetrable to a data breach, taking steps to mitigate damage (and protect customers in the meantime) is crucial. As consumers and governments alike become more privacy-minded, organizations are being held accountable like never before for their handling of sensitive data. These changes are catalyzing a change in the way businesses approach their privacy, with data security posture management (DSPM) becoming a core focus of many organizations’ privacy operations.

Every organization could benefit from taking a privacy-by-design approach (or ‘shifting left’). But there’s also room to start small, with simple measures like enabling multi-factor authentication and data encryption.  

At the end of the day, effective and compliant data governance for Google Workspace users starts with going beyond the perimeter of your Google Workspace, and extending your view – and controls – across your entire data estate.  

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