Nine Best Practices for Efficient Database Archiving - Slide 7

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Once the organization has developed business rules, it needs to test them by simulating what will happen when data is actually archived. A best-practices solution provides simulation reporting that shows database administrators exactly how many records a given archiving policy will remove from the production system and how many will remain because the ERP classifies them as an exception.

Organizations that use prepackaged ERP/CRM, custom, and third-party applications are seeing their production databases grow exponentially. At the same time, business policies and regulations require them to retain structured and unstructured data indefinitely. Storing increasing amounts of data on production systems is a recipe for poor performance no matter how much hardware is added or how much an application is tuned. Organizations need a way to manage this growth effectively.

Over the past few years, the Storage Networking Industry Association (SNIA) has promoted the concept of Information Lifecycle Management (ILM) as a means of better aligning the business value of data with the most appropriate and cost-effective IT infrastructure — from the time information is added to the database until it can be destroyed.

While the SNIA defines what an ILM system should accomplish, it does not specify any particular technology for implementing application ILM. According to Informatica, archiving is one approach that can be particularly effective — if organizations follow archiving best practices to ensure the optimal management of data during its life cycle.

This slideshow features Informatica’s best-practices approach for implementing application ILM archiving.

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