What Is Data Redundancy & How Can You Avoid It?

by | Nov 4, 2020 | Data Science | 0 comments

Data empowers businesses to make effective decisions based on facts instead of guesswork. With the right data in hand, you can shift through the noise and get the right information to make decisions that can fuel your business growth and success. That’s the power of data; it can make or break any business, depending on how effectively it is used. 

When it comes to dealing with big data sets, data redundancy can be a major challenge your organization may face. Servers are the target destination where all your data stays. Therefore, it becomes crucial to ensure that only useful and relevant information is moved there.  

By feeding relevant data to your data warehouse, you can make the best use of your storage space and ensure that not even a single byte is wasted or misused. Let’s learn about data redundancy and how you can avoid it.

What is Data Redundancy?

Data Redundancy occurs when the same data set is stored in two or more places. It may not seem like a big deal until multiple data sets pile up more than once, taking up gigabytes of storage space on your servers. Managing duplicate data when your servers are already loaded can be a grueling process.

Data Redundancy

As the data redundancy increases with time, it will eat up a huge chunk of your server’s storage space. The lesser the storage space will be, the more time the process of data retrieval will take, affecting the overall performance of your business.

Another major reason that makes it more critical for you to look out for data redundancy is that the same data stored in several places can confuse users and make it difficult for them to identify which data they should access or update. There is a higher likelihood that you may end up with corrupt reports or analytics that can cost you your organizational growth.

How can DataChannel help?

DataChannel offers brilliant data warehousing solutions that ensure all your data is integrated into your preferred data warehouse, along with all the customization you need. DataChannel’s data integration technology helps you integrate data from dispersed sources into one place so that duplicate data can be avoided across multiple systems. 

DataChannel also facilitates the cleansing of data as part of the process to save a lot of time and effort. We do everything when it comes to data cleansing like preventing data duplication, removing null values, fixing errors, updating records, and that too in real-time and with data security.

With us, you can reduce redundancies within your existing databases and move forward with your business growth.

What else can you do to avoid data redundancy?

Every business prefers to make a copy of the data intentionally as a form of data security or backup. This seems to be a good idea when you have all the resources required to store and manage your data. If you are facing a scarcity of storage resources, here’s what you must do to avoid data redundancy.

Data Redundancy

Master Data

With Master Data, you can ensure better consistency and accuracy of data. It is the sum of all your business-critical data stored in disparate systems across your organization.

Although master data does not reduce data redundancy, it helps companies understand that it is not practical to expect zero data redundancy and work around a certain redundancy level.

The main benefit of using master data is that in case a data piece changes, the organization, instead of working on the overall data, has only to update that one piece of data.

Deletion of unused data

Another factor that adds up to data redundancy is keeping that piece of data in your server that is no longer required. For example, you moved your customer data into a new database but forgot to delete the same from the old one. In such a scenario, you will have the same data sitting in two places, just taking up the storage space.

To reduce data redundancy, always delete databases that are no longer required.

Design your database

With in-house applications that read from databases, you can design your database’s architecture the right way. The relational databases will ensure that you have common fields and allow you to link up tables and match records. This will make it easier for you to figure out repetition and remove it.

Normalize Database

It is a process in which data is efficiently organized in a database so that duplication can be avoided. It ensures that the data across all the records provide a similar look and can be read in a particular manner. With data normalization, you can standardize data fields, including customer names, contact information, and address. This will help you delete, update, and insert any information with ease.

Data management

Intentional data redundancy in the storage server can help organizations in many ways, but the same can deteriorate your overall organizational efficiency if it happens by accident.

Companies can walk to the safer side of the fence by implementing a reliable data management system. With DataChannel’s data integration solution, you can reduce data redundancy and have only that data in hand that can help your business go a long way.

The Bottom Line

Unplanned data redundancy can be a really big problem for organizations. Therefore, it becomes essential to remove as much redundant data as you can, but be careful while deleting as you don’t want any crucial data piece getting deleted by mistake.

Keep the backup of data only when you need it all back in the same way it was before. With DataChannel’s data integration solution, you can automate the process of data cleaning while the data is being loaded into the target destination. It will help you avoid duplicate data as well as errors and leave you only with the exact data you expected.

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