Data efficiency involves making data easier to access and manage, and requires finding a balance between cost and effectiveness. Storage media and hardware play a significant role in data efficiency, with solid-state hard drives being the most responsive but expensive. Data compression and deduplication can also improve efficiency by reducing file size and eliminating duplicates. Efficient storage systems prioritize frequently used data on high-cost devices and move older archive data to slower, less expensive alternatives.
Data efficiency is the process of making it easier to use, manage, and access data. It’s typically a concern of large-scale enterprises, whose extensive networks and records can easily make the process of finding and using specific data a bit like finding a needle in a haystack. While data efficiency is largely a matter of configuration and configuration—in other words, organizing data in a way that makes it easier to locate and obtain—it also has a significant hardware component. Outdated and inefficient hardware can make the process of extracting data from a hard drive or network much more cumbersome than necessary. For this reason, data efficiency is a trade-off; it requires finding the right balance between cost and effectiveness.
Where the data is stored has a lot to do with its overall efficiency. While solid-state hard drives are often the most responsive places to store data because they can produce and open required files faster than most other storage media, their cost per gigabyte of storage space is relatively high. Older storage media, such as tape backup drives, are quite cheap per gigabyte of storage space, but the trade-off is that their access speed is quite slow. This trade-off between cost and benefit is the crux of building efficient storage systems.
Data efficiency aims to make it easier to access the most frequently used data on the network by placing it on high-cost, high-power storage devices, moving older archive data to slower, less expensive alternatives. This way, people working on the network have faster access to vital data without crippling the organization’s resources and budget. Other techniques involved in making data storage more efficient include data compression, which is the process of reducing files to the smallest possible size, and deduplication, which uses software algorithms to eliminate duplicate files from the network.
Compression and deduplication can free up valuable disk space on a network, further improving efficiency. Like people, computers have a much easier time completing a search when the number of files being searched is relatively small and the average file size is correspondingly modest. By regularly deleting unnecessary files and eliminating excess space within files, the data efficiency of the network is further improved.
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