As Information Technology has found application in almost all aspects of our lives—personal, corporate, public and private sectors alike—there is inevitably a deluge of data. According to IBM, the global volume of data doubles every two years.
The reasons for this exponential growth of data are numerous. For instance, companies nowadays go into all sorts of business analytics in order to understand the psyche of their consumers and of their competitors. This intense research necessitates larger storage and handling of massive amounts of historical data.
The main downside to increased data volume is slow access to data which can ultimately lead to poor customer service
The result of data overload may soon offset its benefits. For one, there is the necessary increase in staff time to maintain storage of these data and the systems upon which it is stored. Additional disk space, floor space and capacity upgrades may have to be required, and all cost money. Perhaps the ultimate downside to increased data volume is slow access to data which may lead to inability to satisfy consumer demands.
The following are some of the best practices for handling data explosion:
A logical database is divided into distinct independent parts to make the data more manageable, accessible and efficient. A popular arrangement would be distributing the partitions into multiple nodes, with each node accessible to a set of users and these users able to perform locally at each node. Together, these nodes work synchronously as a distributed work team, thus increasing productivity.
Data compression, also known as source coding, is the process of using coding schemes to encode data using fewer bits. As a result, total file volume is reduced with the resulting reduction in storage needs and the bandwidth necessary to transmit it. In essence, data compression converts data from the original format into one which has been optimized for compactness. There are two major benefits afforded by this scheme—savings in storage space and increased speed in communication.
Older data which have outgrown their usefulness should be archived to less-costly storage. Closed business transactions and reference data which are not regularly needed for the daily operations are moved to the archive. Data archives, then, are information which are not actively used but may be important for future reference or they may be needed for regulatory compliance purposes. These data archives should be properly indexed and optimized for accessibility and retrieval should they be needed.
Advanced planning for large increases in data should be part of the IT strategy for any businesses reliant on the data stored on its computers or networks. Well managed, efficient and correctly backed up data is an asset to your company. Slow to access, poorly organised data will not only cause day to day headaches with poor access speeds and difficult to find files, but could also prove horrendously costly in the event of a disaster such as a failed hard drive, fire or flood.
A professional data recovery company always have a chance of rescuing your data in these circumstances, but as in all cases, prevention is much better than cure.
