What is data integrity and why is it important?

Data integrity refers to the accuracy, completeness, and safety of a company’s digital assets. Failure to maintain data integrity can have a significant effect on businesses both large and small.

Improper data management in specific industries like healthcare, pharmaceuticals, and financial institutions could result in significant legal trouble. Not only do companies risk losing money via fines, sanctions, or legal fees, but a large-scale data breach can also impact a company’s reputation – including loss of trust that can be difficult to regain. 

Most MSPs and IT techs take a very high-level approach to data integrity. They know they’re supposed to keep data secure – especially in industries with compliance regulations – but few system administrators go much deeper. 

In the article below, we’ll provide a more in-depth look at data integrity. You’ll learn a more specific definition of data integrity, why it’s important, the different types, and more. To start, we’ll explore what data integrity is.

What is data integrity?

Data integrity, by definition, is the process of managing and protecting your client’s digital assets. The techniques and tools you use to ensure a company’s data remains consistent, accurate, and complete make up your overall data integrity – or data protection – plan. 

If you’re successful at maintaining data integrity, the databases your clients use daily should remain secure and reliable. Even in larger organizations, where hundreds of employees access the same data hundreds of times a day, a solid data protection plan should keep potential data leaks and hackers at bay. 

Effective data integrity means securing data from inside first and foremost. Your client’s system won’t be able to handle the continuous barrage of malicious external forces without first ensuring internal users are managing data correctly. Systems to validate and check data, as well as training to educate end-users on data integrity best practices, must be implemented to keep organizations safe.

One of the most popular external assaults on your data integrity, as of late, is ransomware. To learn more about how to protect your clients from the rising trend in ransomware attacks we’re seeing today, download our free threat report: Best Practices in Data Protection Against Ransomware. And, as always, feel free to contact us if you or your clients should have any additional questions.

The fundamentals of data integrity

While the process of data integrity may look different across organizations, its fundamental principles remain unchanged. As an MSP, these five principles should be your “North Star” for protecting your client’s data and measuring the performance of your data integrity services.

The five fundamentals of data integrity fall under the acronym ALCOA. It means that data should be:

  • Attributable – the user responsible for originating the data must be easily demonstrated. Whoever observed and recorded a particular piece of data should be noted and easy to determine.
  • Legible – System users should preserve original entries, ensure data is recorded permanently, and that it’s recorded in a way that’s easy to understand.
  • Contemporaneous – Data should be recorded in a timely manner.
  • Original – Data should exist and be preserved in its original form. 
  • Accurate – Only error-free data should exist on a network, and it should exist in compliance with company protocols and procedures.

Types of data integrity

To provide your clients with an adequate layer of data protection, you'll need to consider two main types of data integrity. Physical and logical integrity both play an essential role in keeping your clients’ networks safe. Let’s explore each of them in more detail down below.

Physical integrity

As the name implies, physical integrity has to do with where data is physically located as it’s transmitted and stored for business operations. Events like natural disasters, power outages, or hacker disruptions all threaten the physical integrity of your client’s data. 

Logical integrity

Logical integrity works alongside physical integrity to protect your clients’ data from digital threat actors and end-user human error. However, logical integrity takes a slightly different approach than physical integrity. The four main types of logical integrity all center around the core philosophy of ensuring data remains consistent as it’s used in different relational databases within your client’s network infrastructure. 

The four types of logical integrity are:

  • User-defined integrity. These are the particular parameters a user sets to protect the data they use most often. Occasionally, company-wide rules may come into play here, but, by and large, these rules are set by the person using the data.
  • Entity integrity. Effective entity integrity relies on creating individual identifiers that system users can associate with each unique piece of data. The goal of categorizing data this way is to ensure no piece of data in a database is listed more than once and that no field within the database is null. This type of integrity comes in handy with relational tables where the same data is used in various ways.
  • Referential integrity. Referential integrity consists of rules embedded into the framework of a database to ensure proper data management. These rules only allow the appropriate changes, updates, deletions, or additions to the database to occur. Referential integrity rules may block inappropriate data, stop duplicate entries, and ensure data accuracy.
  • Domain integrity. These procedures help to guarantee the accuracy of each piece of data within a given domain – the acceptable values a particular column of the database can contain. Domain integrity parameters usually limit the amount, format, or type of data existing within the database.

Why is data integrity important?

Continuously refreshing and updating data to maintain its integrity is important for several reasons:

  • Maintains consistent quality of goods and services
  • Helps companies control data access
  • Removing incomplete or duplicate records can improve overall system performance
  • Quality data leads to more personal, positive customer experiences
  • Creates a larger framework to protect all data throughout its life cycle
  • Keeps user privacy intact
  • Promotes a higher level of user trust and confidence
  • Enables reliable analysis, which, in turn, supports intelligent data-driven decisions
  • Removing inaccurate, old, or duplicate data allows you to streamline the system’s storage capacity

Risks involved with data integrity

Since internal users constantly manipulate and transmit data inside and outside your client’s networks, achieving 100% data security is all but impossible. At some point or another, there will likely be a data breach or leak to some extent. The best thing you can do as an MSP is educate yourself and your clients on the potential risks to get out in front of its source if and when a breach occurs.

The following are the most significant risks when it comes to data integrity:

  • Human error. Internal users aren’t perfect. Occasionally, they may enter data incorrectly, key in duplicate entries, or fail to follow data integrity best practices. While this is one of the more significant cybersecurity threats, a little training and education can go a long way toward prevention.
  • Transfer error. These errors happen when data fails to transfer from one database to another. Users may see data in the destination database and not in the source table, or vice versa. 
  • Corrupted hardware. Internal devices like computers and servers can occasionally malfunction. However, if these device failures happen frequently, it can be a sign that something more serious is wrong with your client’s hardware. These corrupted devices can “glitch” and populate incomplete data, spontaneously limit or deny access to data, or more. 
  • Bugs and viruses. Hackers can introduce malicious files like malware, spyware, and ransomware to your client’s digital network. These files can change, steal, or completely delete data. Fortunately, tools like antivirus and antimalware apps can be effective tools to mitigate this particular risk.

For more information on tools you can use to protect clients from risks like bugs and viruses or to educate yourself on the social engineering attacks human error can cause, check out the resources in ConnectWise’s cybersecurity glossary

How to ensure data integrity

For MSPs, pitching your clients on the importance of data integrity isn’t a tough sell. The challenging part of the job comes when you need to work to help them ensure data integrity internally.

There are five critical steps to helping clients achieve data integrity within their system:

  1. Remove duplicate data. Work with your clients to ensure they have an internal plan for removing duplicate data. Duplicate entries can slow down their overall system and inflate their storage costs. Implementing a strategy to consistently “prune” the network for duplicate data can offset these pitfalls and optimize your client’s data integrity.
  2. Put data quality first. Before focusing on data integrity, you’ll need to verify the quality of data within the system. Ensuring your client’s data is high-quality before you design a data integrity strategy is much easier than managing inaccurate data later down the line. MSPs should be proactive by designing procedures that foster high-quality data generation and collection. It’s also a good idea to review, update, and optimize these procedures regularly.
  3. Provide training. In an effort to proactively address data integrity, data entry should be given the attention it deserves. Education and training on what constitutes proper data entry protocols shouldn’t be overlooked. After all, data entry is where data integrity starts. 
  4. Perform regular data updates. Regularly updating and optimizing your client’s data will only improve their data integrity. Preventing data within the system from going stale is a vital component of an overall data integrity plan. These updates can occur in real-time or on a set schedule. If you choose to run them on a schedule, running these updates during off-peak usage times is advisable.
  5. Verify data. Constantly verifying or validating system data can drastically reduce the impact of human error. Not only will the verification process improve the quality of data internally, but it can also prevent low-quality – or even malicious – data from external, unknown sources.

Data integrity tools

The process of data integrity encompasses many aspects of your client’s overall cybersecurity plan. Putting a serious effort behind your client’s data integrity means providing education to prevent social engineering attacks, implementing robust BDR procedures, launching a strategy for data storage protection, and more. It can be a daunting task but fortunately, there are tools to help.

ConnectWise offers a full suite of MSP tools you can leverage to provide your clients the data integrity services they deserve. We even offer free trials & demos, so you can try before you buy. Find the apps, tools, and platforms that are a perfect fit for your clients and your MSP business at no risk to you.

The ConnectWise team is always within reach, and our mission is to ensure your success. Let us show you what we can do for you and your team.


Data integrity is important because it helps to protect IT networks from malicious attacks like malware, spyware, and ransomware. It also is imperative to maintain data integrity in certain industries like healthcare, pharmaceuticals, and financial institutions. These industries have strict compliance regulations governing how certain data types must be managed and stored. Failure to comply could cost companies hundreds of thousands – if not millions – of dollars in fines and penalties.

The four types of data integrity are:

  • User-defined integrity
  • Entity integrity
  • Referential integrity
  • Domain integrity