Enterprise data center migration, data storage optimization

Data center migration, storage technology is almost the most neglected or ignored. The management of storage devices in many enterprises is usually implemented by the primary members of the operation team. Compared with applications and networks, storage professionals rarely have industry certification. Storage professionals are often ignored in promotion, and in many cases, storage professionals do not have a workable career ladder.

Storage devices are also ignored in IT resource management. Many data centers usually do not make full use of storage space, so that the data they can hold can not exceed 20%.. In other cases, storage devices are also ignored. No one needs to check where the unused storage space is. In contrast, the way they deal with the lack of storage space is to buy more storage devices.
The lesson is also obvious: if the enterprise wants to improve the cost of the data center, it needs to implement the best management practice of storage and other resources.
The following are the six steps that the chief information officer and the data center manager can take to optimize the large data storage.
1. check the stratified strategy of large data
Most data center managers admit that they store much more data than they want. The main reason is to worry that discarding the data that may be useful to the future has a certain impact on the electronic discovery and retrieval of the document. However, none of these can store data in an optimized processing and storage manner.
Data seldom used by enterprises or data that have never been used but may be used for legal purposes can be stored in data centers or clouds, or stored on cold storage devices consisting of tapes and disks which are slow but inexpensive. The fast daily access data that the enterprise must provide can be stored on a high - speed solid state hard disk with high prices. The occasionally accessed data between these two extremes can be residing on a medium speed disk drive.
Enterprises need to determine which data should be stored and then placed there, which will reduce the cost of storage.
2. evaluate the cost of data scalability based on Cloud Computing (relative to local deployment)
The current view is that it would be better to use the lengthwise extension data storage at the cloud end for peak data time, because the enterprise only leased the storage space. However, there may be hidden costs when the enterprise is beyond the normal data storage allocation of the cloud. The enterprise should regularly assess whether it is actually expanding in the cloud, and whether it is cheaper to extend the data vertically than in its own data center.
3. clear the storage resources of the enterprise and evaluate their use
Enterprises in the data center, somewhere in the data center, or somewhere in the field, will find the disk drive that is not fully utilized. If the enterprise does not have a latest IT asset management system that tracks all the assets, it needs to be immediately obtained and started to use. Storage devices should be the first area of concern for enterprises, to see if they are fully utilized or not used at all, so enterprises can see where to improve their utility. If there is an outdated storage resource, it can be cleared.
4. evaluation of enterprise distributed data mart storage
This point is in line with the views mentioned above. Enterprises need to know where their distributed data mart (and storage) are and how to make full use of storage devices. If the utilization of storage devices is greatly reduced, then try to redistribute it to a larger demand area.
5. make edge storage strategy and Practice
The unique feature of edge storage is that most of the storage devices are in the use of robots, artificial intelligence, machine learning and automated manufacturing facilities. Edge storage enables enterprises to temporarily store data in collection points of local data centers, and then upload data when bandwidth becomes more available. This may be a batch night process.
Edge storage management may be a problem, because in many cases, local production engineers or factory workers who do not have knowledge background are required to manage. IT storage professionals need to monitor these storage devices, so that they can monitor the running status of the whole, and to determine which machine generated data stored and what data (such as communication between machines and related business, jitter) and decide whether it should be discarded.
6. policy for the formulation and implementation of data retention
Usually the enterprise reviews a user's data retention policy every few years, and these audits should be carried out once a year. Data preservation and user access rights should be reviewed annually, because the storage capacity of these two aspects is constantly changing. This measure also prompts users to determine which data they want and which data can be discarded.
The ultimate goal of all these big data storage objectives is to optimize the utilization and overhead of storage resources, regardless of whether the resources are deployed inside the data center or in the cloud.