Data Storage Strategy

First and foremost, an organization must have storage strategy, many organizations don't have it and they just keep adding storage as the existing storage runs out. In order to create storage strategy, an organization first must create a data profile. Data profile shows what kind of data is present in an organization.. Then there are local and federal laws about data retention, data protection and data privacy which must be taken into account. EU laws for example don't allow data to be taken outside EU and they have different privacy and data retention rules than the laws in the US. Also, call centers must keep copies of phone calls and customer data for legal purpose. Data kept for legal hold or legal purpose may sometimes be required to be kept indefinitely and in most cases for 7 years. Along with data profiling, capacity management is important to determine trend of storage capacity growth and to predict storage requirements.

Once data profile is created, it will give good picture to the organization what kind of data they have and how it needs to be stored. Data that is required to be kept for legal holds or legal purpose, in most of the cases it doesn't need to be accessed very often and it doesn't need to be available to be accessed immediately, typically it should be accessible within 24 hours. For that type of data, there are several solutions; data archiving hardware or data archiving services. There are pros and cons for using data archiving hardware or data archiving services, but in some cases privacy rules and security policies dictate which one can be used. If data is confidential and organization's security policy says that the data should not leave organization's premises, then on site data archiving hardware is the only solution.

Then there is an application data, which can consist of databases, application logs and other application files. For databases, in most of the cases, storage needs to be fast and responsive. This will be totally different storage than the one mentioned above. In the above case data access time is measured in hours, while production application data needs to be available in milliseconds. This is where storage arrays in the SAN (Storage Area Network) environment are used. Again data profile can be used to determine if an application needs high tier storage array or low tier storage array. The difference in cost between high tier storage array and low tier storage array can be significant since they use different kind of disks and different amount of internal cache.

Sometimes data profile may reveal that the data must be accessible by many different hosts, in which case NAS (Network Attached Storage) can be used. This kind of storage allows multiple hosts to mount same network share.

Data profiling can help to reduce the cost of storage architecture by identifying suitable storage for different type of data and capacity planning can help in predicting the need for new storage. Since most of the equipment is leased these days, dates when the equipment must be returned to leasing company become very important, so this is when data migration strategy becomes very important. Data migration may involve application outages which may mean loss of service to customers, degradation of service (data access is slow) or in the worst cases complete loss of data.

And at the and, something that is related to storage is data protection, which may be in different forms, but backups remain most widely used form of data protection. As part of storage strategy, an organization must prepare for adequate data protection capacity as the amount of storage that needs to be protected is growing.

So good storage strategy must involve data profiling, capacity planning, data migration and data protection scenarios which should be non-disruptive, transparent to end users and cost effective.