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Key Takeaways
- Minor data corruptions can be even more dangerous and costly than a data breach or attack because they often go undetected for long periods.
- Data corruption is usually caused by incorrect, outdated or duplicate data entries, as well as inaccessible files and hardware problems.
- To minimize minor data corruptions, you should automate integrity checks, reduce manual entries, monitor data lineage, conduct regular audits and utilize AI tools.
Data forms the backbone of most companies nowadays. Whether it’s customer information, sales data or marketing analytics, good data provides critical insights that help you plan, compete and prepare for the future.
Therefore, we must be vigilant against insidious corruption. This happens when data is gradually being altered unintentionally, and the data corruption is so small that it usually goes undetected until it’s too late.
These can even be a result of human error, poor configuration or just incorrect data being added — something that doesn’t show up in the radar until a proper audit is carried out.
Over time, these minor data corruptions can erode business value and lead to poor decision-making.
Related: How to Climb Out of the Four Greatest Data Strategy Pitfalls
How dangerous are minor data corruptions?
Instead of a data breach or an attack, minor data corruptions don’t happen suddenly, making it, at times, even more dangerous and costly.
Malware attacks can be detected and responded to immediately. Severe data corruption can be detected, recovered and fixed. However, how do you really fix a problem that is difficult to even detect in the first place?
A few examples of minor insidious data corruptions
Incorrect data entries: Incorrect data entry into a system can cause massive problems in the long run. Imagine a human error causing a wrong entry for a financial transaction, customer information or even inventory data. Such information, if not audited in real-time, will leave the whole business vulnerable to risk.
Duplicates and outdated entries: Another example of human error can include duplicate and outdated entries that had to be deleted or updated but were left untouched. Again, on a surface level, this does seem like a small issue, but in the long run, it can lead to significant operational and financial problems.
Inaccessible files: Some files may become inaccessible or even corrupt when the systems are not updated or data isn’t moved properly.
Hardware problems: Aging hardware, e.g., HDDs and SDDs, can lead to a loss of data or at least cause issues in accessing information. This happens when hardware quality is not monitored regularly and storage devices are not replaced.
Causes of such data corruptions
Apart from simple human error, most of these problems occur because they are difficult to detect. Oversight is usually minimal, and there is no monitoring or evaluation that can detect issues as soon as possible.
Sometimes, legacy systems and outdated tools create issues. There is also an over-reliance on user interfaces and dashboards that might not reveal data corruption.
Related: Bad Data: The $3 Trillion-Per-Year Problem That’s Actually Solvable
Consequences of minor corruptions
The consequences of this hidden data corruption should not be underestimated.
Poor analytics and decision-making: Companies need accurate data on their customers, market segments and sales to make critical decisions and strategies. Wrong information can lead to wasted marketing expenses, poor market alignment and mismanaged customer-product fit, which can be devastating for the company.
Inefficient business operations: Minor data corruption can lead to serious operational problems at almost every level. The biggest cost is the time and effort spent on detecting and then reconciling discrepancies in the data. While the issues are being corrected, a lot of operations might need to be paused or slowed down.
Compliance risk: In many heavily regulated business sectors, such as healthcare, manufacturing, law or finance, even a minor error, regardless of its cause, can result in fines and even legal action. Changes in data might only be documented when it’s too late, complicating audits and leading to unforeseen compliance problems.
Loss of trust: While not deliberate, such issues can lead to a loss of trust among key stakeholders. Operational losses, vendor problems, customer complaints and incomplete compliance can lead to huge reputational damage, loss of revenue and more.
Software and practices to safeguard data integrity
While minor data corruptions are hard to detect, with the right tools and standard operating procedures, we can minimize these problems. As a start, companies need to make data integrity part of employee onboarding and training. This will make sure everyone understands what minor data corruptions are and how it’s a shared responsibility to minimize them.
Automated integrity checks: Basic data integrity tools can be automated and can work in real-time in the background. In case of duplicate entries, file name errors or missing fields, the system can flag them for further scrutiny. This will only work if immediate action is taken and the issues are rectified as soon as they are identified.
Reduce manual entries: Companies should work on a system that minimizes the need for manual entries. Most large companies have already incorporated integrated software that can generate orders automatically, send invoices, maintain customer data and much more. While it’s difficult to completely remove human entry, the less there is, the better protected your data is.
Monitor data lineage: Data lineage is simply tracking the flow of data, understanding its origins, alterations and movements, and observing it in real time. By creating a complete auditable trail of data, it’s easy to identify and troubleshoot problems. It also helps to meet regulatory compliance requirements (e.g., GDPR).
Regular audits: Overall, companies need to adopt a proactive approach to detecting minor corruptions. Regular audits are essential and help to conduct a cleanup and prevent data corruption. This should be part of an IT department’s regular activities.
AI tools: Artificial Intelligence and machine learning have given rise to numerous tools that can detect anomalies 24/7. While false positives are possible, using AI-enabled tools helps to reduce costs and improve detection efficiency, which can then be manually looked at during regular audits.
Related: What Every Business Leader Must Know About Data Management to Avoid a Compliance Nightmare
Despite the name, minor corruptions are not “minor.” If left unchecked, they can gradually and silently erode your company’s data quality, trust among stakeholders, break down regulatory compliance and lead to very bad business decisions.
As part of an overall data protection strategy, companies must invest in data integrity tools, train employees and build a culture of camaraderie where employees look out for one another to ensure minimal data corruption.
Key Takeaways
- Minor data corruptions can be even more dangerous and costly than a data breach or attack because they often go undetected for long periods.
- Data corruption is usually caused by incorrect, outdated or duplicate data entries, as well as inaccessible files and hardware problems.
- To minimize minor data corruptions, you should automate integrity checks, reduce manual entries, monitor data lineage, conduct regular audits and utilize AI tools.
Data forms the backbone of most companies nowadays. Whether it’s customer information, sales data or marketing analytics, good data provides critical insights that help you plan, compete and prepare for the future.
Therefore, we must be vigilant against insidious corruption. This happens when data is gradually being altered unintentionally, and the data corruption is so small that it usually goes undetected until it’s too late.
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