What Is Data Redundancy, and How Can You Reduce It?

By Indeed Editorial Team

Published March 29, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Data redundancy is a common phenomenon within organizations that manage and use considerable amounts of data. This redundancy can benefit organizations by protecting data from corruption, despite its capability of causing data inaccuracy. Understanding data redundancy can help you learn about its positive and avoidable effects and how you can leverage it in the workplace. In this article, we answer the question, "What is data redundancy?", explain how it works, explore the database and file-based data redundancy, outline its benefits and limitations, discuss how to reduce it, and highlight the role of a database administrator.

What is data redundancy?

Many people ask, "What is data redundancy?" Data redundancy involves an organization storing the same data in multiple locations at a time. This happens frequently, especially within organizations that manage or use significant data stores. Data redundancy can occur accidentally or intentionally, depending on the organization's approach to information storage. For example, it may accidentally happen when organizations implement new data storage strategies or systems or move to a central data storage system from a database. This can cause errors during processing and performing transactions. An organization may also implement intentional data redundancy to guarantee data accuracy and protection.

Developers generally advise organizations to store data in multiple places. It's also essential that the organization has a central space for this data or master field to ensure a means for updating all storage locations through a central access point where data is redundant.

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How does data redundancy occur?

Data redundancy results in a positive or negative outcome for an organization. The outcome depends on whether the redundancy is intentional or accidental. One cause of accidental data redundancy is the quality of coding within an organization's data management system, as it can lead to pathway malfunction. This means that information may not update appropriately across the data management system, which can interfere with algorithms and cause disparities in the database.

Intentional data redundancy can occur when data management involves several layers to evaluate the information's accuracy. Data redundancy also happens when the organization has backup storage. Backups act as copies of information to mitigate issues with the data management system or the original database. A data management system usually updates the backup when it updates the original information. This ultimately protects the information from corruption and inaccuracy.

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Database vs. file-based data redundancy

Data redundancy can happen regardless of the system a company uses to store information, including file-based structures and databases. A database is a grid system that keeps related and structured data in the cloud or on a hard drive. Databases are usually digital and are useful for adding and retrieving information. It's generally easy to prevent data redundancy within a database by leveraging management systems, programs, and quality coding.

Alternatively, preventing accidental data redundancy within a file-based system may be more complex. A file-based system gathers and preserves information with less structure. For example, files can be physical documents in a filing cabinet or a computerized variation. Developing duplicate files as applications or customer profiles may allow data redundancy to occur in a file-based system.

Benefits and limitations of data redundancy

There are several benefits and limitations relative to leveraging data redundancy within an organization's data storage system:

Benefits of data redundancy

Here are some of the benefits of data redundancy:

  • Improves information protection: Intentional data redundancy can enhance information protection by protecting the organization's data from breaches. It is also challenging for cyberattacks to target considerable amounts of data simultaneously if all the organization's data are in different locations.

  • Creates data backups: Data redundancy enables an organization to preserve its information when something compromises a data set or copy in its storage system. For example, the organization might back up the same information on the cloud if the hard drive containing the data malfunctions and loses its information.

  • Improves data access speed: Some storage locations may be more easily accessible than others if an organization keeps its data in several locations. This ensures that different users within the organization can access several data entry points and enjoy faster data access speeds.

  • Guarantees data accuracy: A data management system can assess discrepancies by having several locations for the same data, improving the data's accuracy. Different levels of data storage can subsequently enable efficient quality assurance.

  • Analyzes accurately: Organizations that store significant amounts of data typically use it to analyze trends and make reports for a company or a client. This necessitates accurate data, which the company can guarantee through intentional data redundancy.

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Limitations of data redundancy

Here are some limitations of data redundancy:

  • Increases disparities: Preserving data in multiple locations can cause disparities if the information fails to update immediately across all locations. This can happen if the original storage location information changes while the other copies don't, or when a change in one copy doesn't apply throughout the array.

  • Creates opportunities for data corruption: Data corruption occurs when something damages or causes errors in the information during the storage, transfer, or creation process. This means that storing several copies of the same data can create more opportunities for its corruption.

  • Costs more to preserve: Data redundancy is costly to maintain and address, whether it's accidental or intentional. For example, organizations might purchase data management programs and hire data storage experts to limit accidental data redundancies.

  • Creates unusable data: Companies that keep considerable amounts of data commonly use it to evaluate patterns of market intelligence for a company or a client. This means that the results of the evaluation may be inaccurate if there's inaccurate data.

  • Wastes storage space: Data redundancy can lead to using unnecessary storage space, especially if the storage space is expensive. This is because data storage organizations may require additional facilities to store accidental copies of data.

Ways to reduce data redundancy

Here are four ways an organization can reduce data redundancy in its databases:

1. Leveraging master data

Master data is the sole source of common business data that a data administrator shares across different systems or applications. While master data doesn't reduce the incidences of data redundancy, it enables organizations to apply and work around a particular level of data redundancy. Leveraging master data ensures that an organization can update a single piece of information if it changes. This system ensures that redundant data remains up-to-date and offers the same information.

2. Normalizing databases

Database normalization involves efficiently arranging data in a database to ensure redundancy elimination. This process ensures that a company's database contains information that appears and reads similarly throughout all records. Normalizing data typically includes arranging a database's columns and tables to ensure they correctly enforce their dependencies. Various companies have special sets of criteria regarding data normalization, and thus, different approaches to data normalization. For example, a company may wish to normalize a province category with two digits, while another may opt for the full name.

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3. Deleting unused data

Another factor contributing to data redundancy is preserving the data pieces that the organization no longer requires. For example, organizations may move customer data to a new database and keep the same data in the old one. This can lead to data duplication and storage waste. Organizations can avoid this redundancy by promptly deleting the data it no longer requires.

4. Designing the database

Companies can also design database architectures with in-house applications that can read directly from databases. The relational databases ensure that the organization has standard fields and enables it to match up records and link tables. This method makes it easier for the organization to identify and remove the repetition.

Primary duties and requirements of a database administrator

A database administrator is responsible for an organization's data management system, and regularly aim to reduce redundancy. Here are their typical responsibilities:

  • Developing database systems: Database administrators develop database systems of high quality and availability, depending on the organization's specialized role. They also devise and implement databases according to the organization's information requirements and perspectives.

  • Leveraging recovery methods: Database administrators leverage fast transaction recovery methods and backup data. They reduce database downtime and set parameters to enable prompt query responses.

  • Supporting staff members: Database administrators offer reactive and proactive data management training and support to the organization's staff members. They also create and determine access points for an organization's employees.

  • Assessing databases: Database administrators determine, implement, and record database procedures, policies, and standards. They also conduct tests and assessments regularly to guarantee data privacy, security, and integrity.

  • Observing performance: Database administrators observe database performance, execute changes, and apply new versions when necessary. They also prepare and supervise data transfers from an existing data platform to a new one.

  • Developing workload capacity and backups: Database administrators develop the capacity to manage extra workloads if the organization grows quickly and adds multiple new users. They also restore lost information with existing backups if there's a server failure.

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