Comprehensive Data Protection in Data Governance

Your data is a useful resource. Data needs strong controls over its structure, access, and lifetime to be beneficial to your organization. Nearly 70% of chief information security officers (CISOs) anticipate having their data compromised in a ransomware attack, but most security leaders are suspicious about data security. Part of the issue is traditional data-management solutions, which tend to be overly complex with numerous disconnected, redundant processes augmented with point-wise integrations. This random method may reveal infrastructure weaknesses that attackers will take advantage of.

In contrast, proactive data governance offers a comprehensive strategy that saves money and makes it easier to protect your data assets. An essential element of Zero Trust security, this integrated approach to data governance covers the whole lifecycle of your data. Additionally, by reducing the blast radius and limiting an attacker’s ability to move laterally within your network, it lowers the cost associated with a data breach. Microsoft Purview delivers a complete data governance solution designed to help manage your on-premises, multi-cloud, and software-as-a-service (SaaS) data. We’ve put together five guidelines to help you get more value out of your data.

1. Organize all of your data assets into a data map

You must be aware of where your data is kept and who has access to it to protect it. This entails writing in-depth descriptions of all data assets throughout your whole digital estate, detailing data categories, access methods, and owner information. A completely managed data scanning and classification service that takes care of automated data discovery, sensitive data classification, and mapping of an end-to-end data lineage for every asset are ideal. Additionally, you should mark the data with well-known commercial and technical search terms to make it simple to find.

Any data map must include storage, which must comprise technical, business, operational, and semantic metadata. This information comprises columns, data types, formats, and other details that can be easily found by automated data scanning. Automated tagging of items like descriptions and glossary terms should be part of business metadata. Operational metadata can comprise data flow activity like run status and run time, while semantic metadata can include mapping to data sources or classifications.

2. Create a framework for accountability and decision

The roles and duties of each asset must be documented once you are aware of where all of your data is. Respond to these first seven basic inquiries:

• How are our data used and accessed?
• Who takes responsibility for our data?
• How will we react if operational or legal needs change?
• What steps must be taken to revoke access in the event of a role change or employee departure?
• Have we put monitoring and reporting in place to monitor data access?
• How do we manage the lifecycle?
• Are we automating the management of permits to enforce compliance and security?

You should create a thorough lifecycle for data access that accounts for employees, visitors, partners, and vendors as an answer to question number one. Consider the person’s job and the intended use of the data when evaluating what information they may require access to. The level of access needed for each role should be determined by business unit executives.

Your IT and security partners can develop role-based access controls (RBAC) for each employee position and partner or vendor request based on the data gathered. Following that, the compliance team will be in charge of monitoring and reporting to make sure that these controls are implemented. By preventing unauthorized usage and malicious exploitation of permissions, using a permissions management solution can also benefit your organization. Your business can decrease IT workloads, save money, and increase user productivity by automatically identifying unusual alerts.

3. Monitor access and use policies

Documenting each data repository’s policies comes next. Decide who has access to the data, including read-only vs. write-access, and how it can be shared and used by external users or in other applications. Will your company use this repository to store personally identifiable information (PII) such as names, ID numbers, and IP addresses? It is essential to apply the Zero Trust principle of least privilege or just-in-time (JIT) access when dealing with any sensitive data.

The JIT permissions model narrows the attack surface to only those times when privileges are being used, strengthening the idea of least privilege (unlike the all-day, everyday attack surface of standing privileges). This is comparable to the just-enough privilege (JEP), in which a user makes a request outlining the task and data they require access to. The user is provided with a temporary identity to accomplish the task if the request is granted. The identity can be erased or disabled after the task is finished. Another strategy is to create standing privileged accounts and then remove access to them using a “broker-and-remove-access” strategy. When seeking to utilize one of the accounts to access data for a specific time, users must then explain their request.

By keeping a record of each request for higher access, whether it is granted or declined, as well as the date the access was revoked, your business can safeguard itself. All businesses must be able to show auditors and authorities that privacy policies are being followed, especially those that store personally identifiable information (PII). Your business can stay out of problems during audits by getting rid of standing privileged accounts.

4. Data tracking for both structured and unstructured data

Data governance has typically concentrated on corporate documents and emails. However, more strong regulations now demand that businesses guarantee the security of all data. Structured and unstructured data shared on cloud apps, on-site data, shadow IT apps, everything is included in this. Structured data, such as that found in Microsoft Office or Google Docs, consists of precisely defined data kinds with searchable patterning. Anything else, such as audio files, films, and even social network posts, can be included in unstructured data.

Therefore, with such a huge data landscape, should you leave it up to each asset owner to develop their data protections? Creating a matrixed approach to data governance, where security and compliance specialists support data owners in meeting standards for securing their data, is an alternative that some of Microsoft’s users have embraced. In this case, a “common data matrix” is employed to monitor how data domains are utilized throughout your company.

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This might be useful in identifying which parts of your company are allowed to only create data as opposed to reading, accessing, or removing data assets. The source of the data, including any employed shadow IT systems, should be identified by your data matrix. Be sure to record any domains and subdomains that contain confidential or sensitive information that is subject to regulation from the government. Additionally, by outlining roles and duties for each business unit, everyone will be able to understand who is in charge of adding data to systems, who is responsible for it, and who is using specific data for what tasks.

5. Remove any outdated data from your system

Given that most IT staff are already overworked, forcing them to stand guard over huge data lakes is not a formula for security. “Dark data,” which organizations pay to retain but go unused in decision making, is already rising at a rate of 62% each year. How do you determine when a piece of data is no longer helpful to your company?

Data deletion is sometimes the simplest approach to protect it. Less data means lower risk, which is consistent with the Zero Trust idea of “assume breach.” Theft of intellectual property (IP) can be financially risky, but the long-term effects on your brand from the theft of client PII can be disastrous. Businesses are required by privacy rules to preserve PII only for as long as necessary; however, it would be extremely hard to manually keep track of which data need to be deleted. Implementing continuing controls to automatically expire PII or setting up automated reminders for assessing sensitive data to determine whether it is still needed are better ways.

It is simpler to remove data when it is no longer required when you are aware of its lifecycle. You may automate the process by having an integrated data governance solution with clever machine learning capabilities to categorize information as it is created and automatically apply the proper sunset policies. Or, to automatically apply a new label after a retention term, use multi-stage retention regulations.

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