What is Data Archiving?
Data Archiving is a practice that involves moving data that is no longer frequently accessed or actively used from the primary storage system to a secondary storage system. The secondary storage system is typically designed for long-term retention and provides a cost-effective solution for storing large volumes of data.
How Data Archiving works
Data Archiving works by identifying and categorizing data based on its usage and access patterns. Data that is infrequently accessed or considered low-value is selected for archiving. Once identified, the data is moved from the primary storage system to the secondary storage system, typically through automated processes or manual intervention. The archived data remains accessible for future reference and can be retrieved if needed.
Why Data Archiving is important
Data Archiving offers several benefits to businesses:
- Cost savings: By moving less frequently accessed data to a secondary storage system, businesses can reduce the costs associated with primary storage and optimize storage resources.
- Improved performance: Archiving data frees up space on the primary storage system, leading to improved performance and faster access to critical data.
- Compliance and legal requirements: Data Archiving helps organizations meet compliance and legal requirements by securely retaining data for a specified period.
- Data retention: Archiving enables businesses to retain historical data for analysis, reporting, and future reference, supporting data-driven decision making.
- Data protection: By maintaining copies of archived data in a separate storage system, businesses can mitigate the risks associated with data loss or corruption.
The most important Data Archiving use cases
Data Archiving is utilized in various use cases across industries:
- Regulatory compliance: Industries such as finance, healthcare, and government must comply with specific regulations that require long-term data retention and auditability.
- Big data analytics: Archiving historical data allows organizations to perform in-depth analysis and gain insights into trends, patterns, and customer behavior.
- Disaster recovery: Archiving critical data offsite provides an additional layer of protection in case of system failures, natural disasters, or other unforeseen events.
- Legacy system retirement: When migrating from legacy systems, archiving allows organizations to retain access to historical data without the need to maintain outdated infrastructure.
Other technologies or terms closely related to Data Archiving
- Data Backup: Unlike archiving, data backup focuses on creating copies of active data to protect against data loss scenarios.
- Data Retention: Data retention refers to the duration for which data is stored, including active data and archived data.
- Data Purging: Data purging is the process of permanently deleting data from the storage system, typically after it has exceeded the defined retention period.
- Data Lifecycle Management: Data lifecycle management encompasses the processes and strategies involved in managing data from creation to retirement, including archiving, retention, and deletion.
Why Dremio users would be interested in Data Archiving
Dremio users can benefit from incorporating data archiving into their data lakehouse environment:
- Cost optimization: By archiving infrequently accessed data, Dremio users can optimize storage costs and maximize the value of their data lakehouse.
- Performance improvement: With less data to process and analyze, Dremio users can experience improved query performance, leading to faster insights and data-driven decision making.
- Data governance and compliance: Data archiving ensures compliance with regulatory requirements and facilitates effective data governance within the Dremio environment.
- Enhanced analytics: By retaining historical data through archiving, Dremio users can access a comprehensive dataset for advanced analytics and machine learning models.
