What is Data Integrity?

In the modern world, having a good database is the same as being a millionaire. People often compare data with money, as it is one of the most critical assets for the future. The one who has accurate data is going to rule this digital world.

Quantitative data along with good quality and authenticity helps any country in boosting its revenue. Data helps any company in so many ways, be it getting data on a disease or showing personalized ads to users, or knowing their consumer base more efficiently.

It is said, the more accurate data a company has, the more successful it is going to become. But it is also vital to know that just having data is not enough; having clean and authentic, and relevant information is also essential, and that’s where data integrity comes in role.

Data integrity refers to the consistency, accuracy, and reliability of the data stored in any database or a warehouse. The data with a complete structure having all characteristics accurate is said to be data with integrity.

 There are many aspects to the integrity of data like physical integrity, which involves storing and collecting the data authentically, then comes the logical integrity, which includes checking whether the information is relevant and accurate in the specific context or not so overall all the rules which are required to maintain the quality of data comes under data integrity. Without integrity and accuracy, all your collected data is useless to the company, so it’s essential to ensure data protection and its accuracy to increase its performance and stability. Corrupted data can also damage your business sometimes.

It’s effortless to alter data because data is not static. The information you receive comes from various places, and many things can change your data from the site it has been created. In addition, it can be transferred to other devices, altered, and updated by whomever and whenever required.

And ensuring data integrity is not just a one-step process. It has to be checked and confirmed at every step, starting from the model’s design to its final output.

Risks Involved in Data Integrity

The risks involved in data integrity are −

  • Human error − It occurs when humans enter information incorrectly, duplicate or delete the data, don’t follow the rules mentioned, or make mistakes while writing.

  • Transfer errors − When a piece of data is present in the destination but not in the source table of a database used while transferring. 

  • Bugs and viruses − Spyware, malware, and viruses are software that can invade your system, and alter, delete, or steal its data.

  • Compromised hardware − Sudden computer or server crashes, hampering the system’s functions are examples that your hardware is compromised which may then render data incorrectly, limit or sometimes even eliminate access to data, or make it even hard to use.

How to Minimize the Risks of Data Integrity?

These all risks can be minimized using the following tips −

  • Limiting its access and restricting the changes by unauthorized parties in the data.

  • Double verification of data whenever it’s sent and received.

  • Backing up your data every day.

  • Using records to keep track whenever information is altered.

  • Conducting regular internal audits to maintain its accuracy.

  • Using error detection software while transferring.

Updated on: 17-Aug-2021

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