Introduction:

Data deduplication refers to the removal of repetitive or redundant data present in a dataset hence leaving only one copy of such data to efficiently utilize the storage capacity and making the computation faster. It is also known as intelligent compression or one instance storage. This technique is used to ensure that only one copy of the redundant data is saved on to the cloud or any other storage medium and rest of all the copies are replaced with pointers that will point to that one single copy. In the article below, data deduplication is explained in detail.

Working of Data Deduplication:

Data deduplication is in fact a data compression technique, which greatly and effectively reduces the original size of your data. To understand the working of data deduplication, consider any storage medium consisting of three elements ‘1’, ‘2’ and ‘3’. Let us assume that we want to add three more elements ‘3’,’4’ and ‘1’ to this storage medium. Now look at the diagrams below to see this scenario with and without data deduplication:

1,2,3,3,4,1
1,2,3

 

 

Without Data Deduplication

 

1,2,3 1,2,3,4

 

 

 

With Data Deduplication, (The arrows represent the pointers of the repetitive data)

 

In this way, data deduplication looks for the replicas of the same data and then replaces them with their respective pointers hence leaving just one copy of that data.

Types of Data Deduplication:

Data deduplication is of five types, which are listed below:

➢    Source Deduplication- Removing all the repetitive data before backing it up.

➢    Target Deduplication- Removing the redundant data after it has been backed up.

➢    Inline Deduplication- Removing the replicated data while the backup process is in progress.

➢    Post-Process Deduplication- It is done once the backup process is complete and data is saved on a storage.

➢    Global Deduplication- This technique of deduplication is used when you want to back up your data to multiple storage devices.

Advantages of Data Deduplication:

The advantages of data deduplication are listed below:

➢    It helps in identifying the repeated patterns.

➢    It reduces the redundant data to just a single instance.

➢    It saves lots of memory/ storage.

➢    It also increases the network bandwidth.

Disadvantages of Data Deduplication:

The disadvantages of data deduplication are listed below:

➢    In case of file level deduplication, even a small change in a file will create another new instance of the whole file. Same is the case for block level deduplication.

➢    It increases the backup time.

➢    It requires a lot more computational power when it comes to referring the replicated data pointers to their respective storage.

StarWind Deduplication Analyzer:

Once you know how to deduplicate your data, the next thing you would want to know is that which deduplication technique is most suitable for your problem. For knowing this, you need to have a good data deduplication analyzer. StarWind has launched StarWind Deduplication Analyzer to serve such purposes.

It helps its users to evaluate the benefits of deduplication in a fast and simple manner. It also allows the users to find out the compression ratios. The user can then select the best candidate for deduplication based upon these ratios. The main benefits of StarWind Deduplication Analyzer are listed below:

➢    High Speed- Because it works directly on your environment.

➢    Infrastructure Sizing Precision- Because it precisely predicts storage requirements.

➢    Extreme Simplicity- Because no formal training or specialized knowledge is required to use it.

Conclusion:

Now you can efficiently reduce the storage occupied by redundant data by using the technique of data deduplication. StarWind Deduplication Analyzer also solves the problem of finding the data to deduplicate. Therefore, it is absolutely not an issue to remove all sorts of data redundancy now. Hence, you can utilize your storage devices very efficiently and enhance your computational power to a great extent.