Data Integrity and why does it matter?


Nominal Data cvr
Table of Contents


As the saying goes, garbage in, garbage out. A strong analysis depends on data integrity. if the data you’re using is compromised in any way your analysis won’t be as strong as it should be. Data integrity means the accuracy, completeness, and consistency of data throughout its life cycle – from its collection to its storage to its dissemination and usage by decision-makers. 

Data integrity ensures that you can trust your data, which will make business processes more efficient and effective and allow you to make decisions with confidence. Remember, ensuring data integrity will ensure the integrity of the analysis, too!

Exploratory Research Guide

Conducting exploratory research seems tricky but an effective guide can help.

What is data integrity?

Data integrity refers to the accuracy, consistency, and relevancy of the data that’s stored in the database. It is about having confidence in your data. Additionally, It’s about knowing whether the data you have is of high quality and that you can rely on it to be fit for purpose. Having data of high quality will help the business make better decisions by using information that is proven to be reliable. 

Data integrity helps ensure that data isn’t corrupted or improperly deleted and that it won’t get lost due to hardware failure or human error. if the data you’re using is compromised in any way the analysis won’t be as strong as it should be. If the analysis depends on the integrity of the data you are using, then it’s important to ensure that the data you’re working with is accurate.

What makes up data integrity?

Data Integrity has four cornerstones – Accuracy, Completeness, Consistency, and Trustworthiness of data throughout its life cycle.  

  • Accuracy: Is the right data being used at the right time and in the right place? 
  • Completeness: Are there any gaps or missing information? 
  • Consistency: Can different people/teams agree on what information they have and what it means?
  • Trustworthiness: Can you trust the analysis obtained from the data?

When performing any kind of analysis, the data you’re using must be as good as possible to get the best results possible. This means you should make sure your data is as accurate, complete, and consistent as it can be at every stage of its life cycle — from when it’s first created until it’s retired forever or used for something else.

Why is data integrity important?

Data integrity matters to any organization because if the data is inaccurate, they can’t have strong data analysis. Data analytics is all about getting accurate insights from your data. What is the use of insights into your organization’s activity, if they’re derived from inaccurate information?

Firms are collecting an immense amount of data. Securing and maintaining the integrity of the data has become a primary concern. Any data is meaningless if it lacks integrity and accuracy.

Data integrity is important because it –

  • Ensures the data is accurate and complete. 
  • Ensures the data has not been tampered with or corrupted in any way.
  • Ensures all the information in a database is consistent and up-to-date.

For instance, if an organization has multiple records for one person with different birth dates, this would be an example of poor data integrity since the information would not be complete and there would not be consistency in the information shared across all records associated with that person. 

According to a report from KPMG International, Only 38 percent of C-level executives have a high level of trust in their company’s customer data. The vast majority of top management isn’t confident in how their company uses data, analytics, or AI. This reveals a serious flaw in data integrity.

It’s crucial to ensure good data integrity as it affects almost every business process and can have a large impact on business outcomes such as profitability, compliance requirements, growth, efficiency, and innovation.

What are the Threats to Data integrity?

Data can be compromised through

  • Human error – An inaccurate entry or theft of information, Data alteration/diddling, deletion on purpose, and through unintentional or malicious acts. 
  • Transform error – Transfer errors occur when records or individual pieces of information do not get transferred from one location in the database to another, causing inconsistencies in the business systems.
  • Bugs and viruses – Bugs or viruses that enter the system can have a profound effect on the data. Data will be at risk of becoming corrupt. A corrupted piece of data can mean hours spent troubleshooting rather than getting work done. 
  • Hardware failure – Hardware failure problems can lead to data loss or corruption.

It’s important to always remember that data must be accurate if you’re hoping to remain competitive as a business.

See Voxco survey software in action with a Free demo.

How to maintain data integrity?

To maintain proper data integrity, businesses must take certain steps during the storage, transfer, and processing of their data. This includes being aware of how their information systems are designed, who has access to them, and how the business partners use the data they provide. 

Tips for Keeping Data Integrity and Avoiding a Data Diddling

  • Validate data

Before inputting data into the system, always validate that it is accurate. This involves making sure that all incoming data fits within specific validation rules.

  • Remove duplicate data 

The best way to ensure the company’s data integrity is to check every file received against a list of previously processed files. This helps ensure that no duplicate files enter the system.

  • Maintain Current Backup Solutions

Automatic backups can protect against data loss due to file corruption, viruses, or even employee mistakes.

  • Regularly Test Backup Solutions

Routinely test your backup solution’s ability to restore files and folders.

  • Educate the Employees

Educating employees about information security is a critical step in keeping your data safe. Make sure they know how to encrypt sensitive data, how to limit access on shared drives.

  • Use Data Self-Audits

Review data regularly with data self-audits. Check who has access to what, when was it last updated, and are there any obvious errors? 

  • Use Hash Values as Part of Auditing Processes

Hash values can be calculated only once and are unique. Every time data is changed or added to your database. Check the data against its hash value to make sure nothing has been corrupted.

  • Keep Access Controls Up to Date

It’s important to ensure the access control remains up to date. Doing so will prevent unauthorized users from accessing company data.

  • Use Strong Passwords and Change Often

Strong passwords are one of your first lines of defense against data theft.

To sum up, Inaccurate or incorrect data is a major cause of problems with business processes, leading to longer development times, poor quality output, and unnecessary work. Maintaining data integrity can be difficult if you’re not fully aware of what data is being used by your organization. 

Without appropriate checks on your data in place, inaccurate information may slip through unnoticed – causing more problems down the line. Data Integrity is Key to Ensuring that the data can’t tamper. To prevent these issues from occurring, you need to rethink the data integrity of the organization. 

In fact, It’s tempting to view data as something separate from decision-making. Yet, businesses rely on data to make critical decisions every day. Protect your business by putting policies in place that ensure integrity at all levels of your organization. When you establish strong data-integrity policies and procedures, you empower employees with clear guidelines on how to handle sensitive information so they can feel confident in their decisions without fear of accidentally jeopardizing sensitive customer or company information.

Read more