Introduction In today’s data-driven world, storage optimization is no longer optional — it’s essential. Businesses face exponential data growth, rising cloud costs, and increasing compliance demands. Implementing an effective storage optimization strategy for Microsoft 365 and cloud environments ensures better efficiency, lower expenses, and improved performance. 1. What is Storage Optimization? Storage optimization refers to improving how data is stored, accessed, and maintained to maximize efficiency and reduce waste. Techniques like deduplication, compression, and thin provisioning are key to eliminating unnecessary data usage while maintaining accessibility and security. (IBM Whitepaper) 2. Core Optimization Techniques Data Deduplication & Compression Deduplication removes duplicate copies of data, while compression reduces file sizes, freeing up space without compromising quality. (Wikipedia) Thin Provisioning Allocates storage space dynamically, reducing the need to provision full capacity upfront. Tiered Storage / Hierarchical Storage Management (HSM) Moves less frequently accessed data to cheaper storage tiers, such as archival HDD or cloud cold storage. (Wikipedia) Data Conditioning Enhances performance by intelligently organizing and optimizing data paths without modifying applications. (Wikipedia) 3. Microsoft 365 & SharePoint Optimization Best Practices Delete unnecessary versions and old files — Clear the recycle bin and archive inactive data to reduce active storage costs. (Microsoft Docs) Set storage quotas — Define OneDrive and SharePoint limits to avoid unexpected usage spikes. Identify and clean up inactive users/sites — Remove orphaned accounts and unused sites. (Campus Technology) Use ROT analysis (Redundant, Obsolete, Trivial data) — Tools like TeamsFox help reduce unnecessary data, lower costs, and prepare for AI-powered services like Copilot. (TeamsFox) 4. Advanced & AI-Driven Optimization Strategies Recent innovations in AI and machine learning are transforming storage optimization: RL-Storage (Reinforcement Learning) — Adjusts caching, queue depths, and other parameters in real-time, improving throughput and reducing latency by up to 43%. (Research Paper) CNN-LSTM Cache Management — Predicts access patterns and optimizes cache allocation for higher hit rates and reduced costs. (Research Paper) 5. Practical Steps to Implement Storage Optimization Assess current storage usage — Identify active vs. cold data and measure performance. Clean up & declutter — Remove unused files, limit version history, and reorganize content. Automate archival policies — Use lifecycle management to move cold data to low-cost storage. Monitor & track performance — Use analytics tools to detect usage trends and forecast needs. Adopt AI-driven tuning — Leverage intelligent storage management for ongoing optimization. Conclusion By applying these strategies, organizations like Logisam can deliver expert storage optimization services that combine best practices with modern automation. The result is improved Microsoft 365 and cloud efficiency, reduced costs, and better compliance — all while preparing for AI-driven, self-adjusting storage in the future.ere