About data lifecycle management & tiered storage
Data lifecycle management could become complex if proper storage mechanisms are not used. Not all companies can afford faster storage devices like hard drive for all data to be stored. Moreover it is not necessary to spend so much on hard drives for storing data that are not used frequently. The cost per byte of storage of data, for hard disk drives is expensive when compared to low speed storage like optical discs and magnetic tapes.
The data in an organization passes through different phases in its life cycle. All data would have been important at some point in their life cycle. But active data are those that are currently important. Such data should be available to the users access faster than the old data. Hence old data can be moved to slower storage devices and the current data can be held in the faster storage device.
The process of moving the inactive or older data to the slower storage device, if automated would increase the efficiency of the data storage solutions and increase the return on investment for the organization. Achieving such automation should be the goal of a data storage solution. Data management policies should be framed in such a manner to assist in reaching this goal.
If a user accesses an old data then it should be moved to the faster disk drive automatically. The data usage pattern has to be studied closely to find out the type of data that is used frequently and what is not used frequently. Apart from that the existing storage resources in your organization should also be known to use them optimally.
A storage assessment should be done to find out the active files in your organization and how much space they occupy. Based on this information it should be decided where to store that file. Tiered storage is cost effective and hence most of the organization go for this method of storage.
| Choosing an effective data management solution | Different components of a data management process | Effective data management strategies for your organization | Features to look for in product data management software | Groundwork for effective project data management | How to implement a product data management system effectively | Outsourcing your work to professional data management services | Preferred storage for life cycle data management | Pros and Cons of distributed data base management system | Tiered storage and data lifecycle management | Understanding data management concepts | Understanding data management definition | Using the right data management techniques to increase efficiency | What are the data management best practices to follow | What do you understand from the definition of data management | What is data base management | What is product data management |