The volume of data that some companies receive and generate daily can be overwhelming and difficult to comprehend. What is data redundancy and why it matters in data management is a crucial concept to understand in the modern digital age.
This article will explain data redundancy and offer insight into how it affects databases and storage systems. It will distinguish between intentional and unintentional data redundancy and explain how to fix or benefit from it.
What is Data Redundancy
What does data redundancy mean? Data redundancy is usually described as the presence of duplicates within a storage system. This is a standard organizational practice used to ensure that an organization may offer seamless service even during a data breach or loss. The concept of data redundancy may appear in several areas, including file storage systems, computer memory, and databases.
Intentional and unintentional data redundancy
Making a clear distinction between intentional and unintentional data redundancy is crucial. When implemented intentionally, data redundancy aims to ensure protection and consistency in the work of an organization. In such cases, redundant data is kept at different locations as a backup. This is often a part of an organization’s plan in case of disaster recovery.
In contrast, unintentional data recovery is usually a result of operational mistakes. It can appear due to duplicate entries or inadequate data management strategies. This, in turn, results in a loss of efficiency and bloated databases, file systems, and servers.
How data redundancy works
Offering a data redundancy example is one of the best ways to explain the effect of accidental data redundancy. Data inconsistency and data redundancy are often mistaken as the same. Inconsistent data usually occurs as a result of data redundancy.
For instance, the same piece of data appears in multiple places but in different formats. This is a classic data inconsistency scenario that may create unreliable or misleading information within a company’s system. In intentional data redundancy, data entries should be identical, as inconsistencies may lead to different values and result in different problems.
In general, many developers recommend keeping the same data across multiple systems. However, there must be a central master field from where the redundant data can be accessed and updated. If this is not possible, companies risk the occurrence of inconsistent data and remain exposed to big problems in the future.
How intentional data redundancy works
Companies choose to either keep a whole copy of their original data or hold on to selected pieces of data only. They store data on hard drives in two or more places in case the original source gets compromised.
While data redundancy may offer protection against cyber security, companies also use it to increase system functionality. For instance, customer service organizations usually rely on data redundancy for a more seamless workflow. In such organizations offering a prompt response to clients is key, so they store information on multiple systems for faster employee access and quicker updates.
Data redundancy in email archiving
Data redundancy extends its significance in email archiving. In fact, many consider it a must-have in email archiving solutions. In email archiving, redundant copies are seen as reliable backups that give companies peace of mind. Simply said, due to legal and regulatory mandates, some companies prefer to have two copies rather than one.
Fixing Unintentional Data Redundancy
The process of fixing data redundancy in a database is called data normalization. This process is based on standardizing data fields and organizing tables and columns to ensure data is introduced correctly. Data normalization starts with defining what is normal data. Then, databases are accessed to find duplicates and address them correctly. During this process, all the columns and tables are assessed to ensure that all dependencies have been entered correctly.
However, this isn’t a standardized process and differs from company to company. Companies have different needs, and what one company might see as normal might be entirely inapplicable to another. Nonetheless, data normalization is seen as the most efficient way to reduce redundancy in a database.
Benefits and Drawbacks
Assessing the potential gains or losses that a company may enjoy or suffer can best be done by evaluating the potential advantages and disadvantages of data redundancy.
Data redundancy benefits
Intentional data redundancy offers companies a list of potential benefits such as faster updates, seamless workflow, and enhanced security. The following benefits may only be enjoyed by organizations that have a strategic data management plan.
Data Availability and Security
Data redundancy is a helpful asset in cases of data loss or any associated security breaches. It allows organizations to have data copies spread across multiple servers which ensures the integrity of their company can remain intact even in cases of cyber attack and hardware failure.
Data redundancy gives organizations an upper-hand by offering uninterrupted access to valuable data and keeping their business running when one data source becomes compromised. Greater data availability and enhanced security are factors valuable to any business, but they become vital in sectors such as health, finance, e-commerce, etc.
Having data available in multiple locations allows quick access to data from the nearest and most convenient location. This helps enhance overall efficiency, making it easier to accomplish more work without much delay and hassle.
However, data redundancy may also help organizations balance heavy data loads. By distributing data across several servers, organizations that handle heavy loads of data may improve responsiveness. For such organizations, this can be a major asset during peak season.
The greater data availability that data redundancy offers ensures that all employees may access data almost instantaneously. In turn, this makes performing updates seamless. This is also a big advantage for service-based organizations that depend on efficiency.
It’s also worth noting that data management systems may examine sources for potential differences. This is crucial when performing updates as it allows organizations to gain greater data accuracy.
Regardless of the reason for downtime, a company is likely to experience setbacks and possibly a major interruption of workflow when relying only on one set of data. Having redundant data in different locations can ensure that even in the event of a security breach, the workflow is not threatened.
Data Redundancy Drawbacks
While data redundancy may bring several benefits to an organization, understanding its potential drawbacks is also crucial.
Duplicate data requires larger data sets, and naturally, bigger data sets are more complex to manage. Synchronizing data across various systems can be very demanding. Ensuring everything is in good condition will require greater attention to detail and greater overall dedication. And by itself, complexity creates much more room for accidents and errors, which may contribute to further problems.
Higher expenses are usually associated with unintentional redundant data that may occupy much space within servers. This type of data may increase storage fees and result in a higher overall data management cost. As a result, this becomes a heavy financial burden for companies working on a limited budget. For organizations who wish to avoid or eliminate such issues, identifying and eliminating unused data can be a good start.
Data redundancy vs backup
While backup and data redundancy might often be used interchangeably in IT, these are two different terms. While, by definition, a backup holds duplicates of the original information, just as data redundancy, they operate differently, mainly differing in accessibility. While redundant data can be accessed at any point in time, and a backup is set in motion only when a case of complete data loss occurs.
Understanding the meaning behind what is data redundancy can help companies create a more comprehensive data protection strategy. However, it can also make them more aware of the potential negatives of redundant data in their system. Either way, data redundancy is a critical element in every system.
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