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Everything Your Business Needs to Know about Data Redundancy

Without data, businesses don't have access to the much-needed insights they use to calculate future plans, outline strategies, and evaluate the efficacy of certain initiatives. To store the rising volume of data that is needed for data-driven understanding, businesses are increasingly relying on data warehouses and cloud data warehouses.

With the latter and more popular option, every little bit of data matters, as storage often has a direct correlation between the data you host and the overall cost to your business. With that in mind, storing duplicate files can create an unnecessary overhead for companies, increasing their total cloud-related costs and decreasing the efficiency of their data systems.

Data redundancy is the general name given to any data that businesses accidentally store in multiple places within their data systems. Unlike purposeful duplicates, which are data backups, data redundancies are simply duplicated files or pieces of data that take up space without providing any additional value.

In this article, we'll dive into absolutely everything your business needs to know about data redundancy, demonstrate what it is, the leading disadvantages of redundant data, and outline strategies you can use to reduce the occurrence of data redundancy in your business.

Let's dive right in.

What is data redundancy?

Data redundancy is an umbrella term that refers to any duplicated data. Perhaps the same data point occurs multiple times in a dataset. Alternatively, you could have two versions of the same data stored in your system, making one of them redundant. Whenever you store the same data in different places, the data world identifies this as a potential redundancy.

On average, around 25% of all unstructured data that a business stores is redundant. Redundancy often occurs within unstructured data, as conducting a comprehensive analysis is slightly more difficult. However, this figure also includes obsolete and trivial data, which is any data that is no longer useful to your business or is superfluous to your business objectives.

By decreasing the total volume of redundant data that your business stores, you can create a streamlined data system that maximizes every single instance of data storage. Especially if you are using a cloud data warehouse, this approach can lower your costs while optimizing what you gain from cloud-first systems.

What Are the Downsides of Redundant Data?

A few files of redundant data will not have a huge impact on the overall status of an entire data ecosystem. In fact, some argue that redundancy is just another form of backup. While this may be true, the best form of backup is a secure one that's purposely stored in another location, not one that has accidentally appeared somewhere in your data system.

As data redundancy grows in your business, you will begin to encounter a range of problems.

Here are some of the leading disadvantages of letting redundant data build up in your data storage facilities:

  • Increase in data volume - Every duplicated file that you store in your data warehouse represents an unnecessary increase in the total volume of your business data. Considering that the volume of data is increasing at rapid rates every year, businesses that don't tackle redundancies will soon be faced with extreme database sizes. Larger databases are harder to much harder to manage and maintain.
  • Rising costs of data storage  - The vast majority of businesses around the globe are now beginning to move toward cloud data storage. The payment system that these third-party providers employ increases as a business stores more data with them. By storing redundant data, organizations increase their cloud bill without extracting any additional value from the superfluous data.
  • Data corruption - Data redundancy often leads to data corruption, as the data can become damaged during the process of moving through the data pipeline to several locations. With a higher likelihood of corruption, businesses could also face computing errors when employees attempt to execute certain functions. The aforementioned issues can culminate in a reduction of productivity and a decrease in the overall utility of your company data.

Data redundancy is a problem that snowballs over time. While the first few files won't matter, when your business begins to notice problems, you'll likely find an expansive catalog of redundant data that is slowing down your system, consuming resources, and wasting storage space.

How To Reduce the Occurance of Redundant Data?

While there is no single method that instantly eliminates redundant data within your systems, there are a number of methods that you can employ to reduce the likelihood of it from arising, pinpoint any duplicated files, and eliminate them.

Here are some leading strategies to reduce the occurrence of redundant data:

  • Database Normalization - Database normalization allows businesses to arrange all available data into highly structured formats, enforcing certain dependencies to align data with its expected traits. Normalization will help your business to ascertain that data reads similarly across all available records. This process of standardization helps to improve the organization of your data while also bringing any duplicated files into the light for deletion.
  • Monitor Usage - By tracing the overall usage of different datasets over time, you can quickly deduce if there are any data files that are no longer in use. If this is the case, removing this unused data can be an effective way of reducing the overall strain on your system.
  • Automate Where Possible - Another effective method of reducing data redundancy is to automate the ingestion process as much as possible. By changing how your business ingests data and transports it through the data pipeline, there will be less chance that a manual error or duplication glitch will contribute to your redundancy problem.

None of these solutions are overnight fixes to your data redundancy problem. However, each one provides a useful method of decreasing the total number of duplicated files or reducing the likelihood that new duplicate points of data appear in your storage architecture.

Final Thoughts

When left unmanaged, data redundancy can become a major issue for businesses. Especially as we move further into this digital age, companies that understand the disadvantages of redundant data and work to implement methods to prevent duplications from occurring will extract major benefits.

From decreasing the total cost of using cloud infrastructure to increasing the efficacy of your data system, managing storage is a useful way of streamlining data platforms. While many businesses overlook this area of data management, it is an easy way of rapidly increasing how effective your system is and decreasing overall redundancies.

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