Besides ignoring the fundamental principles of IT security, nothing can lead to a cybersecurity breach faster than carelessly handling sensitive data. This problem has been prevalent in recent years. However, it seems to be worsening by the day, given the volumes of data organizations create, process, and store.
Mishandling sensitive data isn’t necessarily a result of carelessness, lack of budget, or an oversight on the part of IT. Any contractor, regular workers, or other individuals authorized to access data that meets the sensitivity threshold can create problems.
But whether they do it intentionally or not, time wasted by mishandling your organization’s sensitive data can get your company in a pickle. Fortunately, automated sensitive data discovery can help.
Understanding Sensitive Data Discovery
In many organizations, only a handful of business professionals know the precise storage location of their sensitive data. Data security and data privacy teams often lack a complete understanding of the location of the organizations’ sensitive digital assets and are reliant on manual input from the business teams to identify where PII (personally identifiable information) resides.
When you can’t immediately account for where sensitive personal data is stored across the organization, you’re asking for trouble. Fortunately, modern, network-based sensitive data discovery can be the best remedy for this.
In essence, data discovery is the process of identifying regulated or sensitive data so that it can either be tracked and protected, or disposed of. The process is among the critical business intelligence trends in the past few years. Moreover, it is a significant priority for most enterprise data security departments due to its vital role in compliance readiness.
The process mainly entails auditing regulated or sensitive data like proprietary or confidential data and protected details like PII or ePHI (electronic protected health information). Through data discovery, security teams can identify such information to protect it and maintain its integrity, availability, as well as confidentiality.
Unfortunately, Organizations are Still Mishandling Sensitive Personal Data
Most companies still don’t pay close enough attention to how they handle sensitive personal data. This places them at risk of cybersecurity incidents and compliance issues. Here are some examples of common data mishandling evident in most workplaces of today:
Software development teams using production cardholder information spread across unsecured systems within their quality assurance (QA) and development environments. This is arguably the most common example. When asked why they have such numerous structured and unstructured database files containing vital data kept in open network shares, most claim that the files contain outdated documents and data. Unfortunately, most don’t realize that dates don’t’ matter when it comes to sensitive data.
Sometimes critical production information finds its way to third-party cloud services, tape backups, as well as disaster recovery servers that operate on different security standards from production. All these are among the most attractive targets for threat actors looking for sensitive data.
Managers in departments like finance and human resources frequently store sensitive data on their laptops or PCs. This is to handle other projects outside work beyond regular work hours. When you ask if their unencrypted devices contain their respective company’s sensitive data, most of these decision-makers don’t believe there’s any. But after a scan, you’ll discover records containing bank account details, Social Security numbers, credit card numbers, and the like. This is a classic example of a ticking cybersecurity time bomb.
Business partners and customers frequently email sensitive PDF files, scanned images, and spreadsheets that contain PII. This scenario is prevalent for organizations outside the United States. These organizations can have a limited understanding of the federal regulations governing the security of sensitive data.
4 Ways Mishandling Sensitive Personal Data Wastes Your Time
Data mishandling has numerous impacts on your organization, including financial implications, productivity concerns, as well as compliance issues. However, modern sensitive data discovery platforms are designed to address all these challenges and save time. Let’s explore how.
Data quality entails the completeness, consistency, as well as accuracy of data assets. It’s almost impossible to imagine working towards high-quality data if you don’t have an inventory of the various databases and systems within the organization.
Many entities are grappling with multiple information silos. So mishandling sensitive personal data means the system will be inconsistent and not in sync. As a result, finding the correct insights for decision-making will take more time.
Fortunately, sensitive data discovery entails precise classification and cataloging of critical business information. It eliminates most inconsistencies to create a more robust data quality approach.
Challenges Identifying, Classifying, and Keeping Track of Sensitive Data
Mishandled sensitive data makes it more challenging to locate, organize, and track the information. All these can be simplified if your stored data is well handled, stored, as well as regularly updated. Clearly, it’ll take relatively more time to sift through poorly organized data sets and information silos.
Fortunately, organizations that are consistent with their sensitive data discovery approach will always have an easier time addressing all these. What’s more, they’ll easily apply the protective controls in real-time according to the dominant contextual factors and predefined policies.
As more sensitive data becomes available, so to have regulations focused on protecting the security and privacy of this data. For example, the European Union’s groundbreaking GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act) have unique data security measures that regulated industries must comply with.
However, compliance becomes an issue when you’re mishandling sensitive data, and you’ll waste more time meeting all the requirements. What’s more, the financial penalties when you violate the legislation can be serious.
But sensitive data discovery will make you understand the persona information in your systems, its origin, where it’s kept, access authorization, and the relevant security measures. This, in turn, saves the time spent conforming to compliance standards.
An aggressive data-driven strategy of understanding the system in which you operate and manage your business is crucial if you want to stay competitive. But when you have a flawed input, the system is most likely to deliver a defective output – garbage in, garbage out.
The condition gets worse as the velocity and volume of data grow rapidly. As a result, you’ll spend more time and resources to deliver the data you need to compete effectively.
Fortunately, automated sensitive data discovery, profiling, and cataloging enable you to comprehensively understand the data you have, and where it resides. You spend less resources manually discovering and classifying that data and can refocus those resources on more value-added activities. As a result, you’ll have a competitive edge.
In the current data-driven business landscape, mishandling your company’s sensitive data could have far-reaching consequences to different aspects of your business. But most importantly, this vice can lead you to waste valuable time that you could have spent on your core competencies and revenue-driving activities.
Fortunately, automated data discovery will help address the hurdles through various data security capabilities like detecting and classifying sensitive data. As a result, you’ll get the most from your data and save more time.
Furthermore, sustainable data discovery solutions like Inventa from 1touch.io can be beneficial as you seek to ensure the highest security level for your sensitive data. 1touch.io Inventa automatically discovers, classifies, indexes, and catalogs sensitive personal information across your organization for a variety of data security and data privacy applications.
The AI-based Inventa™ platform is a network-based autonomous, scalable, and pinpoint-accurate data discovery and classification solution with automated, near real-time discovery, classification, and cataloging of all sensitive data – both structured and unstructured – at the enterprise scale. The Inventa platform takes a zero-trust approach to data discovery and doesn’t rely on error-prone, manual input from your organizational players.