As data becomes increasingly available, businesses that use it to drive decision-making are reaping the benefits. According to McKinsey, data-driven organizations are 23 times more likely to outperform competitors in customer acquisition, nine times more likely to retain customers, and up to 19 times more profitable.

With so much hinging on the power of data, the importance of data integrity can’t be overstated. One error in a dataset can have a ripple effect and impact your business’s most vital decisions. So, what is data integrity? What can you do to combat threats and maintain datasets’ integrity for the benefit of your organization, data subjects, and customers?

Here’s a look at the answers to these questions so you can help your company ensure the integrity of its data.


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What Is Data Integrity?

Data integrity is the accuracy, completeness, and quality of data as it’s maintained over time and across formats. Preserving the integrity of your company’s data is a constant process.

It’s worth noting that data integrity isn’t the same as data security, although the two concepts are related. Data security involves protecting data from both external and internal threats and maintaining the privacy of its subjects. This contributes to the data’s integrity by ensuring it hasn’t been compromised by those threats.

Threats to a dataset’s integrity can include:

  • Human error: For instance, accidentally deleting a row of data in a spreadsheet
  • Inconsistencies across format: For instance, a set of data in Microsoft Excel that relies on cell referencing may not be accurate in a different format that doesn’t allow those cells to be referenced
  • Collection error: For instance, data collected is inaccurate or lacking information, creating an incomplete picture of the subject
  • Cybersecurity or internal privacy breaches: For instance, someone hacks into your company’s database with the intent to damage or steal information, or an internal employee damages data with malicious intent

Related: Data Wrangling: What It Is & Why It’s Important

Why Is Data Integrity Important?

Achieving and maintaining data integrity can save your organization the time, effort, and money it would cost to make a big decision based on incorrect or incomplete data. After all, data-driven decisions can only be as strong as the data they’re based on. If the integrity of your company’s data has been compromised in any way, the negative impact could be long-lasting and far-reaching.

In addition to supporting strong decision-making, data integrity protects your data subjects’ information and image. For instance, you may collect your customers’ personally identifiable information (PII), such as their full name, Social Security number, address, and credit card information. If an error is made to the dataset—whether it’s an accidental typo or a malicious external hacking attempt—your customers’ information could not only end up in the wrong hands, but also misrepresent them.

This can also be the case with first-party data, which is information obtained from tracking your users’ actions or asking them questions. Although this information isn’t as sensitive as their Social Security number, any errors can impact how they’re viewed by the company and, in turn, how they’re interacted with and included in larger trends.

For the sake of your customers, data subjects, and broader organization, it’s in your best interest to attain and preserve data integrity.

Achieving & Maintaining Data Integrity

There are several ways you can achieve and maintain the integrity of your organization’s datasets.

Ensure Data Is Accurate, Complete, and High Quality

The quest for data integrity begins during the collection design phase. Ask yourself: Is my data collection method going to provide accurate information? Can I ensure no data will be missing if I collect it this way? Am I getting the data from a reliable, high-quality source?

After designing your collection method, reassess whether it worked as intended. If not, make necessary changes to its design and recollect. Starting off with data integrity is much easier than remediating erroneous data down the line.

Diligently Check for Errors

Human error is one of the easiest ways to lose data integrity, but it’s also within your control. In addition to checking your work, enlisting others to review it, and being careful, there are tricks that can help you catch mistakes. Something as simple as shading every other row of a dataset can help you keep track of each unique point.

Be Aware of Cybersecurity Threats

A hacker trying to access and damage your organization’s data may not appear as a threat at first. People intent on stealing or damaging data may send a link in an email or text message containing malware, which is activated when you click the link. There are many other ways hackers can gain access to your data, and being able to recognize them can help ensure your data’s integrity is protected.

Communicate the Importance of Data Integrity

If you’re not the only person handling data at your company, educate others about the need to protect the accuracy, completeness, and quality of data, as well as how to recognize and combat potential threats. When everyone understands the importance of data integrity, you can work together to maintain it for the greater good.

Take a Data Science Course

Sharpening your data science skills can have a positive impact on your organization and provide the knowledge to not only protect your data’s integrity, but use it to make a powerful impact. An online course may be the right fit for you if you’re looking for flexibility as you manage your career and improve your skills.

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Dedication to Data Integrity

Data integrity is an ongoing process that requires a daily commitment to keeping your subjects’ information safe and giving your organization’s stakeholders the highest quality, complete, most accurate data on which to base decisions.

Are you interested in advancing your career in a data-driven world? Explore our four-week online courses Data Science Principles and Data Science for Business in addition to our other online analytics courses to learn the language of data and how to effectively use it to tackle business decisions.

Catherine Cote

About the Author

Catherine Cote is a marketing coordinator at Harvard Business School Online. Prior to joining HBS Online, she worked at an early-stage SaaS startup where she found her passion for writing content, and at a digital consulting agency, where she specialized in SEO. Catherine holds a B.A. from Holy Cross, where she studied psychology, education, and Mandarin Chinese. When not at work, you can find her hiking, performing or watching theatre, or hunting for the best burger in Boston.