In a data-driven world, managing the ever-growing volumes of information within an organization has become an intricate challenge. Data archiving is a well-known, powerful solution to efficiently store, organize, and safeguard valuable data while optimizing storage costs.
Data archiving is crucial for organizations as it offers several key benefits. It helps manage data volume efficiently, reduces storage costs, and ensures a lean and agile data environment. Archived data remains accessible, providing valuable historical insights for decision-making and strategic planning. By adopting data archiving as an ongoing practice, businesses gain resilience, innovation opportunities, and improved data governance, positioning them for long-term success in the dynamic digital landscape.
Gaining a thorough understanding of the archival process is vital for achieving successful data archiving. By delving into the key steps involved in data archiving, businesses can harness valuable insights to cultivate a lean and agile data environment. Successful data archiving involves learning about your database and ensuring its longevity and accessibility while paving the path to a more secure and successful future for your organization.
Key steps for data archiving strategy:
- Data Analysis and Classification: Analyze and classify the data within the system. This involves identifying data objects based on their size, relevance, and residence requirements. The classification helps determine which data should be archived and which should remain in the active system.
- Archiving Object Definition: Once the data is classified, archiving objects are defined. An archiving object represents a logical grouping of related tables that can be archived together. It defines the structure and attributes of the data to be archived.
- Data Archiving: The identified data objects are archived from the active system. The archiving process involves retrieving the data from the records back to the graphical user interface (GUI) to access the data. Data archiving can be performed using various techniques primarily standard data archiving, enhancements to standard data archiving and tools, such as Data ASSIST.
- Data Transformation: Archived data stored in SAP proprietary file format This may include compressing the data, and in the case of ILM Retention Manager, applying data retention policies. Transformation ensures that the archived data is optimized for storage efficiency and future retrieval.
- Archival Storage: The resulting data is then stored in an archive storage system and or device that is SAP certified for storing file. These systems are designed for long-term data retention, with considerations for accessibility, durability, and cost-efficiency. Archival storage options may include storage area network (SAN), cloud storage, which can be on prem or on a partner system.
- Archive Info Structures: These are tables designed to enable efficient retrieval or the archived data from the storage system. Metadata includes details like data origin, session details, archiving timestamps, and retention policies.
- Retention Management: Once data is successfully archived, retention management ensures that the data is retained for the required duration according to regulatory or business policies. Retention management includes monitoring archival storage, verifying data integrity, and implementing data disposal procedures when the retention period expires.
- Retrieval: When there is a need to access archived data. The archived data is retrieved from the storage system, through the standard user t-codes on the application server.
- Lifecycle Management: Data archiving is an ongoing process that requires lifecycle management. This involves periodically reassessing the data classification, reviewing archiving policies, and adjusting as needed to ensure optimal data management and system performance.
Data archiving is a transformative process that offers immense value to businesses seeking efficient data management, compliance, and operational excellence. By understanding the key steps involved with the process, organizations can achieve a streamlined data environment. Embracing data archiving as an ongoing process empowers businesses to thrive in the digital age, unlocking the true potential of their data assets for a resilient and successful future.
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