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Understanding Data Deduplication, Its Benefits And Use Cases In Business
When Adam shopped at the retail outlet, he gave his name as Adam Jones. Later, he downloaded the app and created an account on it. But, since he wasn’t sure of shopping from the app, he created an account by the name of A Jones.
It seems like a small thing but what happens is that two customer profiles are created for the same person. Later, when the marketing team tries to use the data for a campaign, their analysis will be skewed. Nothing good comes out of storing duplicate records.
What Is Data Deduplication?
Duplicate data is one of the aspects that reduce data quality. Data de-duplication addresses this issue. This is a comprehensive process that compares all records in a database with each other and identifies records that may be duplicated. The aim is to have a single copy of all the data.
How Does Data De-Duplication Work?
Data de-duplication works by correlating data files and data sets to identify duplicate files. If a duplicate is identified, the duplicate records are removed. Each file is also given a unique data fingerprint. This process usually runs in the backend. It scans files across the volume and identifies repeated patterns. These sections are then moved with special pointers to de-duplicate the file. In this way, it also compresses the data.
In the above example, the two records ‘Adam Jones’ and ‘A Jones’, may have the same mobile number. This will lead to them being flagged as potential duplicates. Data quality rules will then determine how they are to be de-duplicated.
De-duplication techniques can be categorized as inline de-duplication and post-process de-duplication.
- Inline De-Duplication
This refers to checking data at the input stage, comparing it with existing data and de-duplicating records before they are written to the database. In the case of Adam, the system may send out a message saying that he already has an account since the phone number already exists in the database.
- Post-Process De-Duplication
This type of de-duplication takes place at regular intervals. It involves checking all existing records. If duplicates are identified, the two records may be merged and de-duplicated.
Benefits Of Data De-Duplication
Data de-duplication is beneficial for companies of all sizes. For starters, it improves data quality. Did you know that poor data quality costs American companies up to $3.1 trillion each year… Here are some of the benefits of data de-duplication.
- Reliable Database
The first major benefit of data de-duplication is that it makes the database more reliable. Whether it is for inventory management or sales, there is a single golden record that shows the current state. Hence, data-driven decisions have more value.
For example, by de-duplicating all customer records, there is minimal chance of having telesales agents approach the same customer twice. The customer is happier and when results are tabled, the analysis is more accurate.
- Lowered Costs
By removing duplicates, the amount of data storage required is reduced. While de-duplicating office documents, photos and videos can save 30-50% of space, de-duplicating virtualization libraries can lead to space savings of up to 95%.
As the storage capacity size reduces, so does the cost associated with it. De-duplication systems are also run through the entire IT operation. Hence, the amount of infrastructure required also drops. In turn, this lowers the pressure on administrative and management resources.
- Network Development
De-duplicating data makes optimal use of available storage and creates a reliable database that can be accessed throughout the network. Thus, instead of the sales team, accounts team, etc. having fragmented views of customer records, they can access a single, complete profile. In addition to freeing up storage space, this process also releases network bandwidth. In turn, this helps sustain development and improves network performance.
Use Cases For Data De-Duplication
Let’s look at a few use case scenarios for data de-duplication:
- In General Purpose File Servers
These file servers often contain multiple copies of the same data since they are accessed by many users. This may be stored in work folders, team shares, etc. De-duplication helps remove older versions of the data and keeps the database current.
- In Backup Targets
Systems typically take backup snapshots at predetermined intervals even though there may not be a change in data. De-duplicating such files help save space without compromising on the backup.
- In Cloud Storage
De-duplicating files at the source stage aid in migration to cloud storage. The amount of data to be uploaded reduces as does the cost and time taken. This also reduces idle time within the system and allows for a more efficient allocation of resources.
- In CRM Software
Maintaining clean and accurate data is critical for CRM software like Salesforce. De-duplicating data helps achieve higher levels of data quality and thus makes the data more usable. By managing duplicate data across operations, it also plays an important role in compliance with data privacy and protection regulations. The benefits can be seen in the form of better relationships with clients and associates.
- In Virtual Machines
When it comes to application testing and deployment, virtual machines often create data copies. De-duplicating these files helps the machines work more efficiently. It also profiles the data on virtual machines and infrastructure to maximize standardized operating systems. This is especially beneficial in the case of applications that are infrequently used.
Similarly, in the case of Remote Desktop Services, as different users access data, they create copies of it. Most data drives linked to remote desktops are identical. De-duplication allows enterprise access while optimizing resources and storage space. It ensures that all users can sign in simultaneously without a drop in systems performance.
Relying on bad data with duplicates can cost companies up to 12% of their revenue. Eliminating duplicate data makes databases more efficient and useful without compromising on data fidelity while saving costs and efforts. The earlier, this issue is addressed, the better it is. That said, once is not enough. Data de-duplication should always be considered a continuous, ongoing process.