If you are unaware of data mapping, you overlook a critical aspect of cybersecurity. How do you secure your datasets when you don’t have a comprehensive overview? Discover why this technique is crucial to enhancing your security measures.
What Is Data Mapping?
Data mapping ensures the fields in the source dataset correspond to those in the destination dataset. It connects their values and attributes, aligning them despite classification, format or location differences.
Sometimes, information represents the same thing but goes by unique names — such as birth year and age. Storage systems, data capture devices and applications often generate, collect or store these details slightly differently, creating technical hiccups later.
For example, even though age and birth year describe how old someone is, you can’t simply connect these fields — a person born in 1989 isn’t 1,989 years old. This is where data mapping comes in to help you define the relationship between data points.
How It Works
How do you collect information? Where do you store it? Who receives the transfer? Data mapping considers data type, location and flow. Once you define these categories, you match the source fields to the destination fields so they align.
A good rule of thumb is to test the mapped system using a throwaway sample dataset. This way, you can see whether the process will be error-free and make adjustments accordingly. From there, you schedule your migration or integration as planned.
Why It’s Used
You use data mapping to manage and track data. You will likely use it for integration, moving information from one system to another based on predetermined triggers or as part of a scheduled timeline.
Another common application is migration — a one-time transfer where the original database is retired upon completion — because it minimizes duplicates and prevents data loss.
You may also use it to streamline consolidation, transformation or analysis. Whether combining sources, converting formats or evaluating datasets, it helps you keep track of your information assets — the information you define and manage.
The Three Main Data Mapping Techniques
Manual data mapping is the oldest technique. This human-led effort is time-consuming, tedious and prone to human error, so it’s largely been phased out within enterprise-level organizations where expeditiousness is crucial.
Semiautomated data mapping incorporates algorithms, logical models or software into the traditional process. These tools make suggestions, and humans follow through. Their fine-tuning fills in the gaps where context was missed. This strategy is the perfect blend of efficiency and accuracy.
Automated data mapping fully relies on software or algorithms with little to no human oversight upon completion. It’s not exclusively used for large-scale projects — technological advances like artificial intelligence and robot process automation have made it more accessible.
The Role of Data Mapping in Cybersecurity
Data mapping’s role in cybersecurity centers around visibility and management. Protecting a categorized, risk-considerate database is much easier than a messy jumble of misaligned text fields, especially during integration or migration.
Chances are you’ve experienced some adverse effects from a cyberattack, even if you don’t know it yet. The average company takes around 207 days to identify a breach, and another 70 to control it.
Since cyberattack severity and sophistication are increasing exponentially, you must act fast. With tools like generative AI, almost anyone can be a cybercriminal. This is partly why the average data breach cost reached $4.45 million in 2023, up from $4.35 million the year prior.
How Data Mapping Improves Cybersecurity
You can use data mapping to improve your cybersecurity posture in several ways.
Inventory Your Information Assets
You can only protect what you know about. While this notion seems obvious, it’s often overlooked. Firms use less than 20% of the data they generate. Cost is one of the main reasons data sits unused — businesses don’t want to pay to move it across environments.
Using data mapping to inventory your information assets allows you to categorize and prioritize everything you have. This way, you can better strategize how to keep sensitive information from falling into the wrong hands.
Comply With Security and Privacy Laws
If you deal with sensitive data like financial, health or personally identifiable information, you must follow security and privacy regulations. Data mapping makes it easy to prove you’re following regulations if you’re required to disclose how you store and handle these datasets.
Accelerate Your Incident Response
If you have a comprehensive knowledge of what datasets you have and where you store them, you can accelerate your incident response. Once you pinpoint the threat actor’s order of actions, you know precisely what might be compromised.
Conduct In-Depth Risk Assessments
A cybersecurity risk assessment evaluates the likelihood and potential severity of cyberthreats. It is a common tool organizations use to determine where to fortify their defenses and prepare for an attack.
Data mapping can enhance your cybersecurity risk assessments. It helps you determine where your digital information assets are and identify which are most at risk. As a result, you can prioritize the most critical ones.
Data Mapping Challenges You Must Overcome
The complexity and scale of your datasets can complicate data mapping. Consolidation and transformation — removing duplicates and filling in missing values — can help. If size is still an issue, consider prioritizing by risk or sensitivity.
Relevancy is another common mapping challenge. As systems evolve, concepts drift and data flows change, your technique may become outdated. Instead of considering it a one-time occurrence, make data mapping an ongoing activity.
Automation tools can help close the gap, but many lack security. Fortify them against cyberthreats using security and monitoring tools. This way, cybercriminals won’t get insights into where sensitive data is or when your next transfer will take place.
Strengthen Your Security With Data Mapping
Sophisticated cybercriminals know how to slip in unnoticed. It’s easier for them to get away with cyberattacks during data transfer because the security measures are typically weaker than usual. Data mapping is essential for safeguarding source and destination datasets.
