What is Data Duplication?

Last Updated : 27 Feb, 2024

Data duplication is a computational technique that removes multiple copies of data that repeat. If the method is successfully used, storage utilization may be increased, which might save capital cost because less storage media would be needed overall to fulfill storage capacity requirements.

What is Data Duplication?

Data duplication is a technique that lowers storage overhead by getting rid of duplicate data. This techniques guarantee that on a storage medium, such disc, flash, or tape, only one distinct instance of data is kept. A pointer to the unique data copy is used in place of redundant data blocks. Data duplication and incremental backup are similar in that they copy just the data that has changed since the last backup.

How Does Data Duplication Work?

Inline and post-processing duplication are the two main types of duplication techniques. They are designed for various backup situations.
Data in a backup system is analyzed via inline duplication. Redundancies are detected and eliminated during the process of writing data to the backup store. When performing high-performance main storage activities, it is advised to disable data duplication technologies since this might lead to a bottleneck and need less backup storage.
After data is written to storage, redundant data is eliminated using post-processing duplication. A pointer to the data block’s first iteration is used to replace any duplicate data that has been found and eliminated. Users may rapidly recover the most recent backup and deduplicate certain workloads using the post-processing method.
More storage space is needed for post-processing duplication than for inline duplication.

Use Cases of Data Duplication

Resolving identities scalable: The capacity to store and retrieve individual data sets in a compressed manner is essential for entity or identity resolution over big data collections. The use of duplication can streamline, accelerate, and enhance entity resolution procedures.
Virtual Desktop Infrastructure (VDI): Companies may easily supply their employees computers by using Remote Desktop Services and other VDI servers. Such technology may be used by an organization for a number of purposes, such as remote access, consolidation, and application deployment.
Marketing using big data: Businesses that conduct extensive data-collection marketing initiatives stand to gain a great deal from duplication. Big data marketing is ideal for duplication since it necessitates the archiving and storage of all acquired data, allowing for the lossless reduction of file and data sizes.
Cloud storage backup: For businesses with large volumes of data stored in the cloud, cloud storage backups may be quite expensive. By reducing the file size of the data being saved, duplication can result in considerable cost savings.

Advantages of Data Duplication

Reduced expenses: Businesses may maximize the use of their storage equipment by allocating storage more effectively. This can save your company a significant amount of money because you’re not paying as much on hardware updates.
Improved capacity for backups and storage: Since duplication only stores unique data, it is feasible to provide more space for backups and drastically reduce the amount of space required for storage.
Better data recovery: By eliminating superfluous data from the mix, data duplication accelerates backup recovery. It helps keep business continuity plans viable while cutting down on downtime.
Network optimization: Data duplication optimizes storage locally without requiring network transmission. This makes accessible the bandwidth needed to keep the network operating at peak speed, reliability, and performance.

Disadvantages of Data Duplication

Inaccurate reporting: Proper reporting necessitates precise and duplicate-free data. This is hampered by duplicate data. Reports produced from redundant data are less trustworthy and unsuitable for decision-making.
Lack of Personalization: For every business, tailoring experiences for individual customers is crucial. You risk losing clients to other businesses if you don’t take action. Duplicate records can undermine your faith in your data, which will make personalization challenging to use in your company.
Storage Costs: Depending on the type of data you keep, duplicate records may need a lot of space, which might raise storage expenses. Imagine you get an email attachment of one megabyte that was sent by one hundred employees of your organization. 100 MB of storage space will be needed to hold 100 instances of the attachment.
Increases Bandwidth Requirements: Large amounts of network bandwidth are needed when replicating data across several servers. Data transfers between servers might put a load on your network and can raise operating expenses.

Difference Between Data Duplication and Compression

Data Duplication	Compression
Data duplication is a technique that lowers storage overhead by getting rid of duplicate data.	Data Compression is the process of encoding, reorganizing, or otherwise altering data to make it smaller.
In Duplication, the data is grouped according to the shared blocks.	Compression reduces the size of the data file by removing extraneous data, whitespace, etc.
In Duplication Insignificant data loss happens.	In Compression data loss is minimal
Duplication rates can be as low as 4:1, as high as 20:1, and in certain cases, as high as 200:1	Compression can reduce data size to a ratio of 2:1 to 2.5:1.
Hash numbers and pointers cause significant changes to data.	Fundamental information doesn’t change.

Conclusion

In conclusion Data duplication is a technique that lowers storage overhead by getting rid of duplicate data. In duplication, the data is grouped according to the shared blocks. This optimizes storage locally without requiring network transmission. This makes accessible the bandwidth needed to keep the network operating at peak speed, reliability, and performance.

Frequently Asked Questions on Data Duplication – FAQs