Data redundancy is when multiple copies of the same information are stored in more than one place at a time. This challenge plagues organizations of all sizes in all industries and leads to elevated storage costs, errors, and compromised analytics. A typical example of this is customer information that is replicated across departments’ separate systems (e.g., finance, marketing, sales).
How does data redundancy work?
Data redundancy works by causing either positive or negative effects for an organization depending on if it happens purposefully or in error. Accidental data redundancy can occur because of poor coding within a data management system. This can cause pathways to malfunction, meaning data may not update correctly throughout the data management system. This can cause discrepancies within the database and interfere with algorithms.
Purposeful data redundancy works by offering the data management multiple layers with which to assess the accuracy of the information. Data redundancy also occurs when backup storage is present. Backups function as copies of information in case something happens to the original database or data management system. When done correctly, the backup updates when the original information does. This can protect information from inaccuracy and corruption.
What is data redundancy?
Data redundancy is when an organization stores the same information in more than one place at a time. This happens frequently, especially within large companies or organizations that manage expansive stores of data. Depending on the organization and how they manage their information storage, data redundancy can occur on accident or purposefully.
It can occur accidentally when organizations implement new data storage systems, or when they change from using a database to a central data storage system. An organization may choose to implement purposeful data redundancy to ensure accuracy and protection. When data redundancy occurs in error, however, it can cause delays and mistakes during processing and transactions.
Database vs. file-based data redundancy
Data redundancy can occur no matter the system for storing information, include databases and file-based structures. A database is usually a grid system that stores structured, related information on a hard drive or in the cloud. Databases are optimal for adding and accessing information and are almost always digital. By using programs, management systems and quality coding, it can be simple to avoid data redundancy within a database.
Avoiding accidental data redundancy within a file-based system may be more difficult. A file-based system collects and stores information with less structure. Files can be physical documents within a filing cabinet or a computerized version of that. Creating duplicate files as customer profiles or applications is one way data redundancy can occur in a file-based system.
Benefits and disadvantages of data redundancy
There are many benefits and disadvantages to using data redundancy within a businesss data storage strategy. These are some ways data redundancy may affect your information management:
These are some benefits an organization may experience by purposefully implementing data redundancy within their information management structure:
Though data redundancy can have many benefits, these are some disadvantages that accidental or purposeful data redundancy can cause:
Tips for reducing accidental data redundancy
You can use these helpful tips to reduce instances of accidental data redundancy within your data storage systems:
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