Elastic's data tiering strategy aims to optimize data storage and management, enhancing efficiency and resilience for organizations using its platform. Initially adopted for specific use cases, Elastic's flexibility often leads to broader adoption for tasks like logging, performance monitoring, and security operations. As data volumes grow, effective data management becomes crucial to avoid bottlenecks and costly inefficiencies. By aligning data strategies with business objectives, organizations can optimize data storage across different tiers, such as hot, warm, cold, and frozen, to balance performance and cost. A case study illustrates how a customer improved their data management by transitioning to a new architecture that reduces hardware needs, improves data retention, and enhances search capabilities. This strategy enables better log management, license utilization, and the onboarding of new use cases while simplifying platform management and reducing costs. Despite potential drawbacks like slower search performance in frozen tiers, this approach supports evolving business needs and facilitates data-driven decision-making.