Job98456

Age : 45 Joined : 08 Mar 2008 Posts : 1850

Data growth rates are climbing at an astonishing pace. Oracle databases today are holding many terabytes and in some cases petabytes worth of data. In most cases, the data is not deleted regularly even though the new transactions continue to occur within the application. Companies either ignore this issue or resolve it temporarily by adding more space because, after all, “disk is cheap.”

Well, it’s not all about saving disk space. Instead, it’s about truly protecting corporate data for long periods of time in order to meet regulatory requirements. It’s also about achieving maximum performance of applications through a reduced amount of data to process. Not only will applications run faster, but utility functions such as backups, recoveries and reorganizations will execute more efficiently. It’s also about deleting any information that can be legally used against the company. As a result of these, you might also save some disk space.

Archiving data requires creating a strategy for long-term data retention. This strategy is usually determined in collaboration with IT, line of business and legal teams. This strategy could be impacted by one of two types of requirements - internal requirements, where for example a company must keep all customer records accessible and online for a period of 24 months, or requirements that stem from government regulations like Sarbanes-Oxley, HIPAA, PCI, etc. For example, HIPAA requires that medical records be retained up to two years after a person’s death. Sarbanes-Oxley requires audit data be kept for seven years after the conclusion of the audit and CFR (Life Sciences) requires that pharmaceutical companies retain clinical trial data for 35 years. Requirements are extremely stringent for companies that must retain data for legal purposes, and most are not prepared to hold data for such long time frames, let alone guarantee it hasn’t been altered in any way.

The life span of data in Figure 1 begins with data inserted into the operational system that is needed for regular business transactions. Later, it is used primarily for reporting purposes, where decision support and data warehousing applications come into play. This data is often “read only” and highly summarized. When the data is no longer required for quick online accessiblity, it should be moved to a data archive. At this stage, the data can be accessed, just not typically at the same efficiency as within the application. Finally, when the data is no longer required for long-term retention, it can and should be discarded.