Best Practices for Demystifying Unstructured Data Management
Unstructured data has its advantages and constitutes the majority of data created and stored by organizations today. Businesses depend on how this data is used and managed. If critical data is lost, organizations can incur irreparable financial and reputational damages. That’s why managing unstructured information properly and implementing reliable data protection measures is important. This blog post explains how to manage unstructured data to improve operational efficiency and reliability.
Unstructured Data: Challenges and Business Impact
Unstructured data doesn’t have a predefined structure like structured data (databases) and has its challenges when it comes to unstructured data management. Unstructured data is usually presented as files, but emails and other media messages can also be classified as unstructured data.
Volume and variety: Managing growing complexity
The volume of unstructured data is continuously growing, and managing it is becoming more complex. The complexity of data also increases – the number of file formats is high and it is not easy to classify where critical data is stored. If files are unsorted and unnamed properly, managing unstructured data becomes even more difficult.
Large volumes of unsorted and unclassified data can lead to data sprawl. If temporary and unneeded files are not deleted, they consume additional disk space, which is not rational. When data is uncategorized (critical, important, low-important, temporary), it is difficult to select what to back up. Storage systems should be scalable to store the growing volumes of data.
Data quality and lineage challenges
Unstructured data can be outdated, irrelevant, not validated, redundant, etc. These factors make managing unstructured data more difficult. The processes of working with data are dynamic and unstructured data is often migrated between disk volumes, file servers and repositories. Users can modify this data at each stage and it may be challenging to identify its validity and authenticity.
Compliance, security and governance risks
If unstructured data is not managed correctly, security risks related to private data can arise because unstructured data usually contains personally identifiable information (PII). Organizations must meet compliance requirements based on their geographical location and industry. For example, organizations working with the personal data of citizens of the European Union must meet GDPR compliance requirements. If these requirements are not met, fines and penalties are applied to the non-compliant organization.
If users’ private data is not well-protected, security risks can cause data leaks and data loss. If this happens, an organization violates compliance requirements, which can lead to negative consequences. Without proper unstructured data management, it is difficult to define which data is sensitive and must be encrypted and protected.
Using NAS for scalable and secure data storage
Network Attached Storage (NAS) systems are widely used by small and medium-size businesses as centralized storage for unstructured data. NAS devices are convenient, scalable and cost-efficient. They support adding more disks or installing disks of higher volumes, soft RAID for data redundancy and flexible file sharing options. However, NAS devices are desired targets for cybercriminals and ransomware. In case of improper unstructured data management, ransomware can access unprotected files and corrupt them by encrypting them irreversibly.
Best Practices for Managing Unstructured Data
Follow the best practices below to optimize unstructured data management and reduce the risk of data loss and other negative consequences.
Discover and catalog data
Discover all your data stored in different locations – file servers, NAS devices, data lakes, repositories, application data, emails, etc. Log data location, metadata, encryption status, file size, owners, etc. Gathering all information about stored data allows you to get the whole picture of data types and volumes.
Create a detailed catalog of discovered data to ensure complete visibility. Note the data categories, their importance and other parameters. You may need to collaborate with multiple departments because users in each department know which data is important to them. Based on gathered information, add tags and metadata to files to identify data and improve organization of unstructured data. Regularly perform data audits because data can evolve and change over time. Update your catalog/inventory accordingly.
The advantages of using a catalog of unstructured data are:
- Improve data governance – enforce access controls and compliance policies.
- Enhance searchability – users can search for documents by keywords, tags or owners.
- Prevent redundant data storage – identify duplicate or obsolete files.
- Support compliance audits – track access and usage of sensitive data.
Examples of discovered data sorted by source location and use cases:
- On-premises storage: File servers, NAS, local desktops/laptops
- Cloud storage: AWS S3, OneDrive, Azure Blob Storage, Google Drive
- Enterprise applications: CRM (Salesforce), ERP (SAP), HR systems
- Emails and collaboration tools: Outlook, Gmail, Microsoft Teams
- Multimedia & logs: CCTV footage, call recordings, event logs.
Once data is discovered, creating a searchable catalog helps users find and manage it efficiently. You can use metadata to organize unstructured data effectively. It also enhances searchability and classification by adding structured labels to unstructured data. Define what metadata should include. The table below provides examples of metadata.
| Metadata attribute | Example value |
| File type | PDF, DOCX, CSV, MP4 |
| Owner | HR, IT, Finance Department |
| Creation date | 2024-12-10 |
| Last accessed | 2025-01-15 |
| Compliance | GDPR, HIPAA, SOX |
| Sensitivity level | Public, Internal, Confidential, Restricted |
Classify data for better organization
Classify data to improve unstructured data management – discover and identify personally identifiable information (PII) and sensitive data in storage. You can use conventional methods like keywords and patterns for search. Alternatively, you can use advanced software with artificial intelligence and machine learning algorithms to analyze data more precisely with deeper recognition options.
After you discover data, you can classify it based on:
- Business value: Critical, Important, Non-Essential
- Sensitivity level: Public, Internal, Confidential, Restricted
- Regulatory compliance: GDPR, HIPAA, CCPA, ISO 27001
- Usage type: Documents, Images, Videos, Logs, Emails
Establish the proper classification framework for your organization. An example of classification is displayed in the table below.
| Classification | Description | Examples |
| Public | Non-sensitive data available to everyone | Marketing materials, FAQs, public reports |
| Internal | Business data for internal use only | Company policies, internal emails |
| Confidential | Sensitive data requiring controlled access | Employee records, financial reports |
| Restricted | Highly sensitive data with limited access | Legal documents, trade secrets, customer PII |
Organize data using clear file naming and folder structure. Organizing unstructured data in this way makes it easier for users and administrators to navigate and identify data. Below is an example of organized folders with files for a financial department.
/Finance
/2023
/Budgets (Confidential)
/Invoices (Internal)
/2024
/Audits (Restricted)
/Financial Statements (Confidential)
Public data stays in open folders.
Role-based access controls (RBAC) and encryption protect confidential and restricted data.
Establish access governance policies
Implement strong access control measures by establishing governance policies. Data governance manages unstructured data by controlling who can access, modify, share and delete data. Unstructured data can be scattered across multiple storage locations (including on-premises and cloud storage systems) and governance policies are important to reduce security risks.
- Configure role-based access control (RBAC) to ensure only authorized users can access data.
- Follow the principle of least privilege, which restricts user access. Employees can only access the data necessary for their job functions, reducing the risk of insider threats.
- Consider multi-factor authentication (MFA) for access to critical data. MFA adds an extra layer of security by requiring multiple verification steps before granting access.
For example, a finance department user should only access financial reports, while marketing users should not have access to payroll documents.
- Ensure that governance policies for unstructured data management align with GDPR, HIPAA, CCPA, SOX and other regulations and compliance requirements.
- Configure policies to control external data sharing via cloud platforms like OneDrive, Google Drive, etc.
- Consider configuring policies to move outdated data to an archive. This approach frees up space in the primary storage with high performance.
- Use the following technologies to manage unstructured data:
- Identity and Access Management (IAM) (Azure Active Directory, AWS IAM) for user authentication and authorization in the cloud.
- Data Loss Prevention (DLP) (Microsoft Purview, Google Cloud DLP) is used to monitor sensitive data access and transfers in the cloud.
- Privileged Access Management (PAM) to control access to high-risk data and privileged accounts.
- Zero-trust security models for continuous verification of user identity before granting access.
Ensure data backup and recovery with NAS solutions
Back up data stored on file servers and NAS devices to protect shared files and other data. First, back up critical data needed for daily operations. If a NAS device contains backups, consider making a backup copy to improve your data protection strategy and follow the 3-2-1 backup rule. Test backups to ensure that data can be recovered in case of a disaster. Create a disaster recovery plan that includes all the steps required to recover data in different situations.
Use automation for data monitoring and management
You can automate data monitoring and management to improve security, compliance, performance and operational efficiency. Consider automatic storage tiering to store frequently accessed data on high-performance storage of a higher tier and move rarely used files to low-performance (lower-cost) storage of lower tiers. You can use the lowest tier for archived data. You can also configure lifecycle policies to automatically move old data to the archive.
Continuous data monitoring helps detect unauthorized access, performance issues and potential security threats. Track real-time data access logs and usage patterns to detect unusual activity (for example, deleting or modifying a high number of files in a batch). Configure alerts and automatic notifications to interact and fix issues in time. Automate data backup and disaster recovery workflows.
How NAKIVO Simplifies Unstructured Data Management
NAKIVO Backup & Replication is a dedicated data protection solution that supports backup of unstructured data stored on file servers, NAS devices and Windows or Linux machines (servers and workstations). The NAKIVO solution supports backups of NFS and SMB file shares, which is especially convenient when backing up files shared on NAS devices and file servers.
- Full and incremental backup. Ensure reliability and storage savings. Full and granular recoveries are supported.
- Storing backups in different locations – local backup repositories, tape, NAS devices, cloud storage, including AWS S3, Azure Blob Storage and S3-compatible object storage.
- Backup encryption. Source-side backup encryption protects data against interception during data transfer over the network and protects backups stored in a repository from unauthorized access. You can enable network encryption and encryption at the repository level if needed.
- Immutable backups. Enable immutability to protect backups against ransomware and unauthorized data deletion and alteration.
- Microsoft 365 backup. Microsoft 365 services contain unstructured data, such as emails, OneDrive files, Microsoft Teams messages, etc. The NAKIVO solution supports Microsoft 365 backup. You can back up the needed Microsoft 365 services, users and objects and perform full and granular recovery to the source or a custom location.
Conclusion
Unstructured data management helps improve overall operational efficiency and reduce various risks related to security, data protection and compliance. Follow best practices that include data discovery, classification, access control, data governance policies, and data protection. Protect unstructured data stored on-premises and in the cloud and store multiple backup copies in different locations. Use NAKIVO Backup & Replication to back up and recover data effectively.
