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Our Criblpedia glossary pages provide explanations to technical and industry-specific terms, offering valuable high-level introduction to these concepts.
Data tiering is a data management strategy that involves organizing and storing different types of data based on their usage patterns. It consists of moving less frequently used data, or cold data, to lower levels of storage or tiers. This process allows organizations to optimize their storage systems and infrastructure, reduce costs, and improve overall performance.
Originally, “data tiering” comes from shifting data between different storage levels in a storage system. Nowadays, it includes transferring or storing data between other cloud or storage systems, facilitating seamless movement and accessibility.
Data tiering has two primary classifications.
Hot Data
Hot data refers to an organization’s most critical and frequently accessed data. It includes real-time transactional data, such as customer information and financial records. This data must be readily available for fast access and processing to support business operations.
Cold Data
Cold data refers to infrequently accessed or inactive data not regularly used in day-to-day operations. This may include historical records, logs, and backups. While this data is still essential to keep, it does not need to be stored on high-performance storage systems.
Tiered Data Storage
Data tiering involves categorizing data into different tiers based on its importance and usage. This allows organizations to store data cost-effectively using various storage technologies, such as SSDs for hot data and tape or cloud storage for cold data. With tiered data storage, organizations can ensure that their most critical data is stored on high-performance systems while less important data is stored on lower-cost solutions.
Data tiering uses a policy-driven approach to automatically move data between tiers based on its usage. This process is typically performed by software-defined storage solutions that constantly monitor and analyze data usage and then move it to the appropriate tier.
First, data is categorized into hot and cold tiers based on usage. Hot data remains on high-performance storage systems for fast access, while cold data is moved to lower-cost storage solutions.
Next, data can be further classified within each tier based on its importance or sensitivity. This helps organizations prioritize data storage based on performance and cost, optimizing system resources effectively.
Finally, data is continuously monitored and analyzed to ensure it is in the most appropriate tier.
Implementing DDAA involves integrating with existing data systems, establishing strong data governance, and ensuring quick search capabilities for efficient data retrieval.
Integrated Systems
DDAA integrates with your current data systems, ensuring that you can manage and access your data without major overhauls to your existing IT infrastructure.
Strong Data Governance
It’s crucial to have clear rules and procedures for managing your data with DDAA, to keep your archived data both safe and functional.
Quick Search Capabilities
DDAA comes with powerful tools to find and retrieve data efficiently, so your archived data can be found and used with ease.
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