Statista predicts that the data created, consumed, and stored globally will reach 180 zettabytes by 2025. Handling the growing amounts of data your business generates—and avoiding pitfalls and problems scaling to meet that demand—requires a well-defined data classification strategy so you can make informed decisions regarding data storage, access, and sharing.
But not all data is equally valuable. By classifying data based on attributes such as sensitivity, value, and whether it is subject to governance, risk, and compliance (GRC) requirements, you can establish clear, efficient guidelines for how long each data category should be stored and retained.
For example, sensitive customer information may require extended retention periods due to regulatory requirements, while non-critical operational data might require shorter retention periods. Ultimately, sound data classification enables you to reduce storage costs, minimize clutter, and ensure compliance. For your reference, the ASEAN Data Management Framework stipulates in its guidelines that data management policies should clarify how your organization handles data to internal and external stakeholders.
The Consequences of Ineffective Data Classification
You could expose your business to significant risks if you don’t have a solid data classification system. Here are some examples:
• Inability to differentiate between critical and non-critical data means your storage resources could be overloaded with redundant or outdated information, wasting precious IT budget.
• Without proper classification, your business may struggle to identify data subject to retention requirements, leading to noncompliance and potential legal repercussions.
• Poor data classification often translates to poor data security management. Without clear guidelines on handling data, your employees and partners may inadvertently mishandle sensitive information, ignore encryption protocols, share it with unauthorized users, and store it on devices that aren’t well secured.
One major obstacle to establishing effective data classification policies is the sheer volume and diversity of data generated across your business operations. Data may also be stored in different formats, file types, and locations. That makes the process more complicated and can lead to misclassification. Finally, a lack of employee awareness and training regarding the importance of data classification can also slow adoption.
Four Steps to Effective Data Classification
With that in mind, here is a data classification guide that can help you ensure easier access, enhanced security, and improved decision-making:
1. Establish a Cross-Functional Team
Assemble a task force involving IT, data management, legal, and compliance experts to define clear data classification criteria that ensure your classification system meets regulatory requirements and supports business goals.
2. Invest In Automation
Data management and classification tools and solutions that automate the process can scan and analyze data to assign appropriate labels and tags based on predefined rules. Automation offers many advantages, including dramatically reducing the potential for human error—a common problem in manual classification efforts.
The result will be higher accuracy in data classification and a reduced likelihood of sensitive information being mislabeled or improperly handled. Finally, automation ensures a consistent classification standard across diverse data sources and types, eliminating discrepancies arising from human interpretation or judgment variations.
3. Invest In Training and Awareness
Educating your employees regarding the importance of data classification, the potential risks of mishandling data, and proper procedures for accurately classifying data is vital. Doing so enables you to foster a culture focused on responsibly handling data throughout your organization.
4. Adopt a Dynamic Strategy
Data classification isn’t a one-and-done deal. It’s an ongoing task that demands continuous monitoring and adjustment. Your business—and the world—don’t remain static, nor does your data. Proper classification requires periodic reviews and updates to accommodate changes in data types, regulatory requirements, and business needs. Regular audits and assessments can identify areas where classification may have deviated from standards or when new data categories have emerged.
An effective data classification strategy empowers your organization to harness the true potential of its disparate data and replace chaos with clarity.
Protect Your Data Properly
Because Arcserve offers the broadest set of best-in-class solutions to manage, protect, and recover all data workloads, from SMB to enterprise, regardless of location or complexity, you can count on finding a solution that cost-effectively covers every data classification type.
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