Data Management Glossary
Data Storage Optimization
Data storage optimization is the process of improving how data is stored to maximize efficiency, reduce storage costs, and enhance performance. Historically data storage optimization has focused on storage management strategies and technologies designed to minimize the amount of physical storage used while ensuring quick access to data and maintaining data integrity. In the AI era, there is been a greater focus on unstructured data management and delivering data storage management services (DSMS) that separate the storage from the data to deliver both infrastructure optimization and unlock data value.
Strategies for Data Storage Optimization
- Data Deduplication: Eliminating duplicate copies of data can significantly reduce the amount of data stored, especially in backup systems where the same data might be saved multiple times, but also email storage and cloud storage.
- Compression: Reducing the size of data by using algorithms that eliminate redundant information. Compressing files (e.g., zip or gzip) reduces the storage footprint, which can lead to significant space savings, especially for large or repetitive datasets such as log files, media files, and archival data storage.
- Thin Provisioning: Allocating storage on demand rather than pre-allocating it allows you to allocate more storage to applications than what is physically available, assuming that not all of it will be used immediately. This reduces wasted storage and is commonly used in virtual environments and cloud services.
- Tiered Storage (see Data Tiering): Storing data on different types of storage based on its importance or access frequency. Frequently accessed (hot) data can be stored on high-performance, expensive storage (like SSDs), while less accessed (cold) data can be moved to slower, cheaper storage (like HDDs or cloud archives). Tiered block storage is common for databases and large-scale enterprise data storage. Read: Block Level Tiering versus File Level Tiering.
- Data Archiving: Moving infrequently used data to long-term, cost-efficient storage. Regularly archiving old data to low-cost storage (such as tape drives or cold cloud storage) is a well known strategy to free up space in more expensive, high-performance systems. Legal records, research data, historical logs are common examples of data that is archived as it often has to be retained for regulatory and compliance reasons.
- Storage Virtualization: Pooling physical storage from multiple devices and managing it as a single resource. Virtualization simplifies storage management, increases utilization rates, and enables more flexible data distribution across storage devices. Cloud storage environments and data centers often deploy storage virtualization strategies.
- Use of Solid-State Drives (SSDs): Replacing traditional hard disk drives (HDDs) with SSDs, which are faster and more reliable. SSDs significantly improve read/write speeds, reducing latency, and boosting overall system performance. High-performance applications and virtual machines often rely upon SSDs.
- Erasure Coding: A data protection method that breaks data into fragments, expands and encodes it with redundant data pieces, and stores it across different locations. This provides more efficient data protection than traditional RAID setups, reducing storage overhead while ensuring that data can be recovered even if part of the storage system fails.Use cases include: Distributed storage systems and cloud storage.
- Cloud Storage Optimization: Using cloud-based services to store data, with intelligent policies to manage what data is stored locally vs. in the cloud. Cloud storage can offer elastic scalability, allowing enterprises to store massive amounts of data at a fraction of the cost of physical storage. Some cloud providers offer tiered storage solutions that automatically move data to lower-cost storage as it ages. Data backups, disaster recovery and business applications increasingly rely upon cloud cost optimizations solutions.
- Storage Efficiency Tools: Using software tools to analyze and optimize data storage. These tools can identify underutilized storage, provide automated tiering, and offer analytics to forecast future storage needs. These tools often integrate with virtualization platforms and cloud providers to deliver insights. Use cases include storage monitoring and proactive capacity planning.
- Automated Data Management and Policies: This means you’re able to automate the movement of data based on usage patterns and business rules, which allows organizations to automate data lifecycle management, like archiving or deleting old files, ensures that only active or important data consumes valuable storage resources. Enterprise file systems and cloud storage providers work with software solution partners like Komprise to deliver analytics-driven unstructured data management solutions.
What are the Benefits of Data Storage Optimization Services?
- Cost Savings: Reducing the amount of physical storage needed, especially in large environments.
- Improved Performance: Faster access to data by eliminating bottlenecks caused by inefficiencies.
- Simplified Management: Easier storage management due to intelligent policies and reduced data footprint.
- Data Security: Improved data protection, backup efficiency, and recovery capabilities.
- Budget Available for AI: The 2024 State of Unstructured Data Report found that “preparing for AI” remained a top data storage and data management priority for IT leaders. Yet leaders said that cost optimization is an even higher priority this year as they are try to fit AI into existing IT budgets. Only 30% say they will increase their IT budgets to support AI projects. Read the press release.
Effective data storage optimization balances performance, costs, and data accessibility, ensuring that businesses can scale efficiently. When it comes to growing file and object data in the enterprise, both It and line of business teams are increasingly looking to unstructured data management solutions like Komprise to deliver cost savings and to unlock greater data value.
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Komprise Intelligent Data Management is focused on delivering data storage agnostic data storage optimization and data mobility software solutions.