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Key Takeaways
- Small data corruptions can be more dangerous and costly than a data breach or attack because they often go undetected for long periods of time.
- Data corruption is usually caused by incorrect, outdated, or duplicate data entries, as well as inaccessible files and hardware problems.
- To minimize minor data breaches, you should reduce integrity checks, manual inputs, track data generation, perform regular audits, and use AI tools.
Data is the backbone of most companies today. Whether it’s customer data, 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. When this data is gradually changed accidentally and the corruption of the data is so small that it is usually not discovered until it is too late.
They can even be the result of human error, poor configuration or simply adding the wrong data – something that doesn’t show up on the radar until a proper audit is done.
Over time, these small data breaches can erode business value and lead to poor decision-making.
Related: How to Survive the Four Biggest Data Strategy Hurdles
How dangerous are small data breaches?
Instead of a single data breach or attack, small data breaches are suddenly, sometimes even more dangerous and costly.
Malware attacks can be detected and responded to immediately. Severe data corruption can be detected, recovered, and corrected. However, how do you really solve a problem that is hard to even detect in the first place?
Here are a few examples of small insidious data breaches
Incorrect data entries: Entering wrong data into a system can cause massive problems in the long run. Think of a human error causing a wrong entry for a financial transaction, customer data or even inventory data. Such data, if not verified in real time, will leave the entire business vulnerable to risk.
Duplicates and outdated entries: Another example of human error, which should be deleted or updated, but not touched, but not touched. Again, on a surface level, this seems like a minor issue, but in the long run it can lead to significant operational and financial problems.
Documents unavailable: Some files may become inaccessible or even corrupted if systems are not updated or data is not transferred properly.
Supply problems: Older hardware, such as HDDs and SDDSs, can cause data loss or at least cause data retrieval problems. This means that hardware quality has not been regularly monitored and storage devices have not been changed.
Reasons for such data breaches
Other than simple human error, most of these problems are difficult to detect because they are difficult to detect. Control is generally minimal and there is no monitoring and evaluation that can detect problems in the shortest possible time.
Sometimes, legacy systems and outdated tools pose a problem. Overreliance on user interfaces and dashboards that fail to detect data corruption.
Related: Bad data: A $3 trillion problem that can actually be solved
Consequences of petty corruption
The consequences of breaching this confidential information should not be underestimated.
Poor analytical and decision making: Companies need accurate information about their customers, market segments, and sales to develop strategies. Bad data can lead to bad market alignments and unmanaged customer product fit that can destroy a company.
Inefficient business operations: Small data corruption can cause serious operational problems at almost every level. The biggest cost is the time and effort involved in detecting and then reconciling data inconsistencies. Even if the issues are fixed, many operations may need to be interrupted or slowed down.
Compliance risk: In many heavily regulated business sectors, such as healthcare, manufacturing, law or finance, even a small mistake can nevertheless result in fines and even legal action. Changes to data can only be documented when they are too late, complicated, and cause unexpected compliance problems.
Loss of confidence: Unintentionally, such issues can lead to a loss of trust among key stakeholders. Loss of operations, vendor issues, customer complaints, and poor compliance can cause significant reputational damage, lost revenue, and more.
Software and practices to protect data integrity
Small data corruptions are difficult to detect, and with the right tools and standard operating procedures, we can minimize these problems. As a start, companies should do the data integrity and training part of the employees. This will make sure everyone understands what minor data breaches are and how there is a shared responsibility to minimize them.
Automated integrity checks: Basic data integrity tools can be automated and run in real-time. If there are duplicate entries, filename errors, or missing fields, the system can flag them for further investigation. This will only work if immediate action is taken and issues are rectified as soon as they are identified.
Reduce manual inputs: Companies should work on a system that minimizes the need for manual inputs. Most large companies include an integrated program that can automatically create orders, send invoices, store customer information, and more. While it’s difficult to completely remove human access, the less, the better your data is protected.
Control data generation: Data lineame simply follows the flow of data, understands its origin, changes and movements and observes it in real time. By creating a complete data trail, it’s easy to identify and troubleshoot problems. It also helps meet regulatory compliance requirements (eg GDPR).
Regular inspections: In general, companies should adopt a proactive approach to detect minor corruption. Regular checks are important and help clean up and prevent data corruption. This should be part of the IT department’s regular activities.
AI Tools: Artificial intelligence and machine learning have led to numerous tools that can detect anomalies 24/7. Using AI-powered tools helps reduce costs and improve detection efficiency if false positives are possible, which can then be reviewed manually during regular audits.
Related: What every business leader should know about data management to avoid a compliance nightmare
Despite the name, petty corruptions are not “petty”. Left unchecked, it can gradually and silently degrade your company’s data quality, erode trust between stakeholders, regulatory compliance, and lead to very poor business decisions.
As part of an overall data protection strategy, companies should invest in data integrity tools, train employees and build a culture of camaraderie where employees look out for each other to ensure minimal data corruption.
Key Takeaways
- Small data corruptions can be more dangerous and costly than a data breach or attack because they often go undetected for long periods of time.
- Data corruption is usually caused by incorrect, outdated, or duplicate data entries, as well as inaccessible files and hardware problems.
- To minimize minor data breaches, you should reduce integrity checks, manual inputs, track data generation, perform regular audits, and use AI tools.
Data is the backbone of most companies today. Whether it’s customer data, 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. When this data is gradually changed accidentally and the corruption of the data is so small that it is usually not discovered until it is too late.
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