What is data integrity? The Harvard Business School defines data integrity as “the accuracy, completeness, and quality of data as it’s maintained over time and across formats.”
What Can Go Wrong?
“When a business fails to look after customers’ data, the impact is not just a possible fine. What matters most is the public whose data they had a duty to protect.”
These are the words of U.K. (ICO) commissioner Elizabeth Denham. It is in response to a $23.8 million fine on Marriott International, Inc. in 2020.
The ICO ruling says Marriott failed to put “appropriate technical or organizational measures in place to protect people’s data.” This is in accordance with the pan-EU General Data Protection Regulation (GDPR).
In 2018, the New York Times reports that the Marriott hack is the target of a coordinated effort by Chinese intelligence-gathering operators.
Earlier that year, an attempt to access the guest reservation database for Marriott’s Starwood brands is flagged. However, the initial breach occurred in 2014, two years prior to Marriott’s purchase of Starwood. According to the story, it potentially exposed the data of as many as 500 million customers.
Is Data Integrity What It Sounds Like?
Yes. Data Integrity is vital to building and maintaining trust among an organization’s customers, partners, and team. Obviously, ensuring data accuracy, quality, and security is vital. Additionally, identifying data-related issues that could affect operations is essential to the prolonged success of an organization.
Joshua Joseph is the manager of data integrity for the xOps team for LMS and GEM in our role for a global travel and leisure organization. He is in constant contact with our partner’s leadership with a running update on data integrity.
“In a span of about two weeks, we validate close to around one hundred thousand guests,” he said recently. “In years past, if you look at the statistics, the number of guests with data-related issues was close to eighteen or nineteen percent. GEM has brought it down to zero-point four-five percent (0.45). Those are the statistics from last week, and that’s a very good accomplishment.”
Key to the success of the GEM team is communication. Without fail, if an issue arises, they immediately ensure the entire team is aware.
“I believe the expectation is to exceed customer and client expectations,” said LMS and GEM Senior Applications Support Analyst Carlos Sarmiento. “Specifically, the culture at LMS is that of accountability. There are no excuses. You own your individual results.”
When LMS was contracted as part of a global project several years ago, as many as 50 other vendors participated. Remarkably, there are now four.
“We are the only team that has actually gotten bigger,” Sarmiento attests. “That is a testament to the work that we do. Our communication skills, our responsibility, and our accountability.”
What is Data Integrity?
Nearly a decade of extensive data science and analytics for Fortune 100 global enterprises has shown LMS the value of self-reliance. Simply put, interacting with LMS is interacting with one entity without the outside influence of a board of directors. It breeds a healthy culture of communication.
According to a McKinsey & Company survey, intensive users of customer analytics are 23 times more likely to outperform their competitors in new customer acquisitions and nine times more so in customer loyalty.
Expanding or upgrading on demand is essential to data integrity. Increasingly, the LMS team proves its ability to expand roles, including into other industries.
“I believe we can do more, in the sense of interacting the experience with other platforms within the projects,” Sarmiento adds. “We can further expand our use with other microservices we aren’t currently handling.”
“The amount of data we can handle, automation, and validating data in bulk,” Joseph adds. That’s the focus. We are working on those technologies to get everything automated because that saves a lot of time. We can go beyond to advance what the client needs. I think that’s a vision we all share.”
The Harvard Business School names four primary threats to data integrity:
Human error: Accidentally deleting data, for example.
Inconsistencies across formats: Such as an Excel file that may not work in a different format.
Collection error: Inaccurate or incomplete data collected.
Cybersecurity or privacy breaches: Someone hacking into a database with malicious intent.