Data redundancy refers to storing the same data in more than one place. This happens in nearly every business that doesn’t use a central database for all its data storage needs. As you move away from siloed data, you will likely come across redundant data. Duplicated information does not only make your database inconsistent but can also significantly skew your data insights, leading to less efficient or unsuccessful business decisions. The following sections introduce you to a quick guide to data redundancy and how you can reduce it.
What is Data Redundancy?
Redundancy is an engineering term that refers to creating systems so that they don’t fail. In web hosting, data redundancy is a strategy that ensures that you never lose any data.
Data redundancy might seem very similar to backups, but redundancy and backups are not interchangeable terms. A backup is, to put it simply, a duplicate copy of your data. Irrespective of how many backups of data you make, where you store them, or even how you create the backup, to begin with – backups are still just duplicate copies of existing data.
Redundancy, on the other hand, is more than just duplicating data. It’s a proactive action plan that you design so that you never lose data. Backups are a part of an overall redundancy plan.
When data is lost from your web server, your website can crash, and you can lose important customer information, business details, and even records of financial transactions. All these are crucial for your business, and therefore, data redundancy should be a top priority.
How does it work?
Data needs to be stored in two or more places for it to be considered redundant. If the primary data becomes corrupted, or if the hard drive the data is on fails, then the extra set of data provides a fail-safe the organization can shift to.
The redundant data can be either a whole copy of the original data or select pieces of data. Keeping select pieces of data enables an organization to reconstruct lost or damaged data. Hard drives with copies of data are stored in an array, so if something happens to the original data, the array can kick in with little to no downtime. In addition, redundancy measures can be accomplished through backups or RAID systems.
Advantages of Data Redundancy
Although data redundancy sounds like a negative event, many organizations can benefit from this process when it’s intentionally built into daily operations.
- Alternative data backup method: Backing up data involves creating compressed and encrypted versions of data and storing it in a computer system or the cloud. Data redundancy offers an extra layer of protection and reinforces the backup by replicating data to an additional system. It’s often an advantage when companies incorporate data redundancy into their disaster recovery plans.
- Better data security: Data security relates to protecting data, in a database or a file storage system, from unwanted activities such as cyberattacks or data breaches. Having the same data stored in two or more separate places can protect an organization in the event of a cyberattack or breach — an event that can result in lost time and money, as well as a damaged reputation.
- Faster data access and updates: When data is redundant, employees enjoy fast access and quick updates because the necessary information is available on multiple systems. This is particularly important for customer service-based organizations whose customers expect promptness and efficiency.
- Improved data reliability: Data that is reliable is complete and accurate. Organizations can use data redundancy to double-check data and confirm it’s correct and completed in full — a necessity when interacting with customers, vendors, internal staff, and others.
Disadvantages of Data Redundancy
When not for an explicit purpose (e.g., data backup, data security), redundant data causes problems. The list of data redundancy disadvantages is long. Key reasons to avoid data redundancy are that it:
- Allows for data corruption caused by damage or errors sustained during the process of storage and transfer of data across multiple locations
- Increases data maintenance costs by requiring multiple copies of the same content to be maintained with costly data management programs
- Increases discrepancies between data that is stored in more than one location (i.e., often updates are made to one version and not to the others)
- Slows down the essential functions of a database, complicating its usage for certain tasks, including data retrieval
- Wastes valuable storage space by saving the same data on multiple systems, which may start small, but can grow quickly
Ways to reduce Data Redundancy
Here are four ways an organization can reduce data redundancy in its databases:
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.
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.
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.
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 repetition.
All in all, redundant data refer to the same information stored in various formats, tables, or systems. Apart from increasing your data storage costs, data repetition is unreliable when it is unintentional since you will most likely use it to make business decisions.
It is important to run checks to delete repeating data, but intentional data redundancy has numerous advantages, too, including enhanced protection. You can also use backups as part of your disaster recovery plan.
Finally, if your company has different databases, it is recommended to opt for data integration to combine all of the data sources into only one database. This will be easier to maintain, cost less, and it ensures that you have access to all the key data for decisions by accessing only one system.