Data Management Glossary
File Analysis (File Storage Analysis)
File analysis or file storage analysis is the process of evaluating and managing the storage of digital files within an organization or on a computer system. The goal of storage analysis is to optimize file storage resources, improve data accessibility, and ensure efficient use of data storage infrastructure.
Gartner Peer Insights defines File Analysis (FA) products this way:
“File analysis (FA) products analyze, index, search, track and report on file metadata and file content, enabling organizations to take action on files according to what was identified. FA provides detailed metadata and contextual information to enable better information governance and organizational efficiency for unstructured data management. FA is an emerging solution, made of disparate technologies, that assists organizations in understanding the ever-growing volume of unstructured data, including file shares, email databases, enterprise file sync and share, records management, enterprise content management, Microsoft SharePoint and data archives.”
Read: Komprise Names Top File Analysis Software Vendor by Gartner
Komprise Analysis: Make the Right File Data Storage Investments
Komprise Analysis allows customers with petabyte-scale unstructured data volumes to quickly gain visibility across storage silos and the cloud and make data-driven decisions. Plan what to migrate, what to tier, and understand the financial impact with an analytics-driven approach to unstructured data management and mobility. Komprise Analysis is available as a standalone SaaS solution included with Komprise Elastic Data Migration and the full Komprise Intelligent Data Management Platform. Read: What Can Komprise Analysis Do For You?
Why File Data Analysis?
File storage analysis is the process of evaluating and managing the storage of digital files within an organization. The goal of storage analysis is typically to optimize file storage resources and cost, improve data accessibility, and ensure efficient use of storage infrastructure. Some common file storage analysis use cases include:
- Storage Capacity Assessment: Determine the total storage capacity available, both in terms of physical storage devices (e.g., hard drives, SSDs) and cloud storage services (e.g., AWS S3, Azure Blob Storage). This assessment helps in understanding how much storage is currently being used and how much is available for future use.
- Storage Usage Analysis: Analyze how storage space is being utilized, including the types and sizes of files stored, the distribution of data across different file types, and the storage consumption patterns over time.
- File Data Lifecycle Management: Implement file lifecycle policies to identify and manage files based on their age, usage, and importance. This includes data archiving, data deletion (See: Data Hoarding), or file data migration to different storage tiers as they age or become less frequently accessed.
- Duplicate File Identification: Identify and eliminate duplicate files to free up storage space. Duplicate files are common in many organizations and can waste valuable storage resources. Watch a demonstration of the Komprise Potential Duplicates Report.
- Access and Permission Analysis: Review and audit access permissions to files and folders to ensure that only authorized users have access. This analysis helps enhance security and compliance with data privacy regulations.
- Performance Optimization: Analyze storage performance to ensure that data retrieval and storage operations meet performance expectations. This may involve optimizing file placement on storage devices, load balancing, and caching strategies.
- Cost Optimization (including Cloud Cost Optimization): Evaluate the costs associated with different storage solutions, including on-premises storage, cloud storage, and hybrid storage configurations. Optimize storage costs by selecting the most cost-effective storage options based on data usage patterns.
- Backup and Disaster Recovery Analysis: Ensure that files are properly backed up and that disaster recovery plans are in place. Regularly test data recovery processes to verify their effectiveness. It’s important to analyze your data before backup to optimize data storage and backup costs.
- Data Retention Policy Compliance: Ensure that data retention policies are adhered to, particularly in industries subject to strict data compliance regulations (e.g., healthcare, finance). This involves safely deleting files that are no longer needed and retaining data as required by law.
- Storage Tiering and Optimization: Implement data storage tiering strategies to allocate data to the most suitable storage class based on access frequency and performance requirements. This can include the use of high-performance SSDs for frequently accessed data and slower, less expensive storage for archival purposes. Read the white paper: File-level Tiering vs. Block Level Tiering.
- Forecasting and Capacity Planning: Predict future storage needs based on historical data and growth trends. This helps organizations prepare for increased storage requirements and avoid unexpected storage shortages. See FinOps.
The right approach to file storage analysis involves the use of specialized data management and storage management software and tools. Read more about the benefits of storage-agnostic unstructured data management. The goal is to deliver insights into storage usage, performance metrics, and compliance with storage policies in order to make informed decisions about storage investments and ensure that file storage is efficient, cost-effective, and aligned with business needs.