Data is growing faster than even the world’s largest organizations can manage, and growing alongside it is IT spending. IDC’s Global DataSphere estimates that up to 90 percent of enterprise data is unstructured, including business content like invoices, contracts, resumes, presentations, videos, and emails. This explosive growth in unstructured data is driving increased data management expenses, including server maintenance, cloud storage fees, and data protection software.
However, organizations can effectively manage unstructured data growth and reduce costs through data minimization and continuous data management. But with all their other priorities, why storage cost optimization?
- Financial efficiency: By eliminating wasteful spending, organizations can free up funds for other crucial business areas and reinvest them in product development, go-to-market initiatives, people development, and other areas that can give them a competitive edge.
- Risk mitigation: In addition to saving money on storage costs, optimizing storage reduces risk. Organizations can enhance their security and eliminate potential vulnerabilities by eliminating stale data. This can prevent costly breaches and can help protect brand reputation.
- Operational efficiency: Through optimal storage and data management practices, organizations can gain a clearer view of their data and use these insights to streamline processes, improve product and service delivery, and drive business growth.
Here are three actionable tips to minimize unstructured data and optimize your data storage costs:
- Discover and Eliminate Stale Data: By implementing a data minimization strategy, organizations can identify and remove redundant, obsolete, or trivial (ROT) data (often called stale data). Data waste requires additional storage capacity and increases security, compliance, and legal risks (the more data, the greater the chance of issues arising). The best place to start is by taking inventory of data across an organization’s cloud and on-premises repositories. Key attributes like Created Date, Last Modified Date, and Last Accessed Date can help organizations easily discover unnecessary documents and files that are no longer needed without deleting essential data.
- Migrate Cold-Tier Data to Archival Storage: Significantly reduce storage fees by migrating infrequently accessed or modified data (sometimes referred to as cold-tier data) to low-cost archival systems like Amazon S3 or Azure Blob Storage. This strategy is especially beneficial for organizations with many infrequently accessed documents and files that cannot be purged due to data retention policies or regulations. By moving such data to more cost-effective storage, organizations can save on cloud or on-premises file repository expenses while adhering to applicable retention policies.
- Control Data Growth with Continuous Management: Implement a continuous data classification and management plan to monitor and proactively act on unstructured data growth effectively. Your plan should include workflows, notifications, and automated policies based on data age, usage, and sensitivity. When implemented correctly, organizations can achieve several benefits, including optimized storage capacity, enhanced data security, and reduced IT overhead.
Optimizing Unstructured Data Management for Budget Efficiency
Effective data management is crucial to minimize the impact of unstructured data growth on IT budgets. Implementing strategies such as data minimization, file migration, and continuous data classification and management can significantly reduce storage costs while maximizing resource utilization. Organizations can proactively manage unstructured data growth by leveraging the right tools and technology, ensuring cost savings, data security, and compliance.
If you’re ready to take control of your unstructured data but aren’t sure where to begin, contact us for a free data discovery assessment.
