Information Lifecycle Management (ILM)

Information lifecycle management key features

Although most organizations have long regarded their data as one of their most valuable corporate assets, only recently has the amount of data under management become a major issue. Originally, data was used to help achieve operational goals to run the business, but as technology capabilities have grown, ever-larger databases have become feasible for both operational - OLTP - and analytical - Data Warehouse - cloud or on-premises applications.

Regulatory requirements are also changing how and why data is being retained, as many organizations are now required to retain and control much more information for much longer periods. These requirements often extend beyond structured data - typically stored in relational databases such as Oracle Database – to semi-structured and unstructured data such as medical images, videos, photos, contracts, documents, etc. The result is an explosion in the amount of data that organizations are required to obtain, organize, manage, and store securely (and safely), while still providing easy, scalable, and high-performance access.

Consequently, organizations are trying to store fast-growing quantities of data for the lowest possible cost while meeting increasingly stringent regulatory requirements for data retention and protection.

The Oracle Database contains a rich feature set that can help implement an Information Lifecycle Management solution and meet the data storage demands:

• Oracle Advanced Compression allows you to seamlessly move data to the appropriate storage tier and compression tier based on its activity level
• Oracle Advanced Compression works across all storage tiers to reduce the amount of disk space data requires
• Hybrid Columnar Compression, on Oracle Storage, dramatically increases storage cost savings
• Works at the database level with no application changes
• Reduces disk space requirements for all types of data
• Allows you to automate the movement of data to lower-cost storage based on activity patterns
• Lowers query times by keeping only active data on high-performance storage
• Increases availability of critical information on the most reliable storage