What is data availability?
Data availability is a term used by computer storage manufacturers and storage service providers to describe how data should be available at a required level of performance in situations ranging from normal through disastrous. In general, data availability is achieved through redundancy involving where the data is stored and how it can be reached. Some vendors describe the need to have a data center and a storage-centric rather than a server-centric philosophy and environment.
Availability concerns both the accessibility and continuity of information. Data that is not accessible quickly can prevent the delivery of services, costing an organization time and revenue.
Different approaches can be used to achieve data availability, including storage area network and network-attached storage. Data availability can be measured in terms of how often the data is available -- a vendor may promise 99.999% availability, for example -- and how much data can flow at a time.
Data availability challenges
There are a handful of challenges that affect data availability. These include:
- Host server failure. Data becomes unavailable if the server the data is stored on fails.
- Data quality. Data that is redundant, inconsistent or incomplete can be useless to IT operations.
- Legacy data. Outdated data can become unusable.
- Storage failure. Data becomes unavailable if the physical storage device fails.
- Network crashes. Failure on the network side means any data accessed through it will become unavailable.
- Slow data transfers. Data transfers could be slow depending on where the data is stored and where it is used.
- Data compatibility. Data that works in one environment may not be compatible with another.
- Security and data breaches. Malicious actors could obtain and block access to an organization's data, such as in a ransomware.
Best practices for managing data availability
Best practices to follow to combat data availability challenges include:
- Redundancy and backups. Backing up data is an essential aspect of data availability. Data backups should be stored in separate locations or in a distributed network. This way, if data is lost or corrupted, it can be restored quickly. Storage devices are often set up in a redundant array of independent disks (RAID) configuration.
- The use of data loss prevention tools. DLP tools can help mitigate data breaches and damage to data centers.
- Erasure coding. This data protection method breaks data into fragments, expands it and then encodes it with redundant data pieces. The data is then stored across a set of different locations or storage devices. If a drive fails or data becomes corrupted, the data can be reconstructed from the segments stored on the other drives.
- Following retention policies and procedures. If data or devices are no longer needed, they should be either archived or securely disposed of.
- Automatically switching to backups. Flexibility can be added by automatically switching to a backup or failover environment if a drive fails or data is lost.
Is erasure coding a replacement for RAID? Learn the differences between erasure coding and RAID and the role each plays in protecting data in the cloud.