Data Lifecycle Management

Data lifecycle management (DLM)

When assessing their cloud model, organizations should take the following two items into consideration: 

Item No. 1: DLM

To better plan and manage storage in cloud environments, organizations must efficiently use their resources by placing data on the most appropriate tier of storage that meets service delivery requirements and then eliminate data that's no longer needed. For example, a healthcare provider who just admitted an emergency patient will need to access the patient's recent records quickly. This type of Tier 1 data should be stored on high-quality, faster media storage, while the patient's older records may be archived on tape (which is slower to access). Either way, the cloud service should provide a range of service-level options that balance performance and costs based on the expected use of the stored data.

Organizations also need to ensure that their data is segregated to ensure that confidential information doesn't get into the hands of others, even in a disaster recovery scenario. Organizations should also ensure that they have applications that provide reporting tools that identify where data is located and can sort by access or saved dates, owners and numerous other filters; automation of data migration between multiple tiers of storage based on policies to move unneeded data from primary storage systems, and transparent operations to minimize impact on other key operational processes.

With these tools, organizations can set policies to take appropriate action or move unnecessary data that clog storage systems and run up usage charges. This automated migration creates a more efficient operating environment, reduces administrative costs and the need to acquire extra hardware.