The Necessity of Mainframe Data Discovery and Classification | 1touch Insights

Exploring the Importance of Mainframe Data Discovery and Classification

Despite years of predicting mainframes’ obsolescence, they’ve remained the backbone of data storage and have grown more useful as data has become highly valuable.

Mainframes have demonstrated adaptability in the face of major transformations, meeting the demands of web, mobile, and now AI-driven applications. It’s unlikely we’ll see the death of the mainframe anytime soon. 

However, mainframes often use data sets that can be challenging to accurately discover and classify to keep data protected — remaining fully compliant and secure. Considering 90% of credit card transactions occur on a mainframe, effectively classifying and securing data is crucial.

Organizations with mainframes must adopt the right platform capable of monitoring, discovering, and classifying all data stored on mainframes to avoid a data breach or non-compliance penalties.

We’ll be exploring how mainframes are used in the modern world, the challenges they present, and the benefits of accurate data discovery and classification for unique data sets used by mainframes. 

What is the Role of the Mainframe in the Modern Enterprise?

As a massive data source, they’ve become more valuable for training AI algorithms, generating insights from company or customer data, and empowering leading-edge marketing campaigns.

However, the rising value of data has also resulted in malicious actors trying to gain access to it, alongside comprehensive regulatory requirements for how specific types of data must be protected. 

We’ve seen mainframes called obsolete, so how prevalent are they in the modern world? One study found that 71% of Fortune 500 companies still rely on mainframes — they’re far from going the way of vacuum tubes.

Additionally, some enterprises have pursued hybrid mainframe environments. While these environments provide plenty of benefits, they also introduce new attack vectors that may put inaccurately classified or hidden data at risk.

Organizations need the right tools available to discover and accurately classify mainframe data — but that presents a unique challenge: VSAM data sets. 

What Are VSAM Data Sets?

A VSAM data set is uniquely formatted compared to non-VSAM data sets. This data set is a collection of records grouped into control intervals. From there, the control interval is a fixed storage space in which VSAM records are stored.

Why does this create a challenge for data discovery? VSAM data sets can only be accessed using the VSAM method. As a result, many existing tools and platforms for data discovery lack the necessary capabilities to access VSAM data sets, which means this data may not be properly classified and protected.

Companies dependent on mainframes can rest easy with Inventa, knowing these data sets are monitored, classified, and protected. 

Why Mainframe Data Discovery is Critical

Data privacy and protection is a significant focus for many organizations, and for good reason — the combination of the rising risk of a data breach and regulatory requirements requires effective data management practices.

Data discovery is the first step in protecting sensitive data to keep it out of reach of cyber attackers and meet compliance requirements. Once discovered, data will then be classified, which in turn dictates how it should be protected according to data management guidelines.

Since mainframes commonly use VSAM data sets that can only be accessed by VSAM access management. Companies that use mainframes and this data set require a data classification tool capable of accessing and evaluating VSAM data sets.

Without the right capabilities, VSAM data may remain hidden in data classification tools. It’s vital to have platforms available that can autonomously discover all data on mainframes to keep them safe, prepare them for usage with AI platforms, and keep the company compliant.

Business Benefits of Effective Data Discovery and Data Classification

How does mainframe data discovery and classification help your business? We’ve already touched on some benefits, but let’s dive deeper into how adopting the right platform can profoundly help your business. 

Data Protection and Compliance

We’ve touched on the benefits of data protection and compliance with data discovery and classification, but how exactly are these benefits created? Let’s break down the connection.

Data discovery is the process of finding data throughout the IT ecosystem. Any newly created or otherwise unclassified data needs to be identified. Otherwise, sensitive data that should fall under data protection policies may remain easily accessible.

Once discovered, data must then be classified. The exact classification categories for your organization will vary based on your organization’s specific requirements, compliance requirements and internal needs.

Classified data will then be protected based on your existing security protocols. Sensitive data will fall under high-security protocols, while other data can be less protected without inviting risks, which is how data discovery results in data protection.

What about compliance? Different regulatory requirements dictate data protection and privacy protocols that must be in place, like HIPAA, PCI DSS, and GDPR. Based on your specific compliance requirements, you’ll need to adequately protect all company and customer data while also being able to prove your protocols to auditors —  and VSAM data sets are not exempt.

Always Stay Secure with AI-Driven Monitoring

New data is created and stored frequently for modern businesses. Data discovery and classification may have been feasible with manual processes in the past — but those days are long gone.

Businesses of all sizes generate massive data, ranging from customer orders to patient records to employee information. Data can be stored on your mainframe, cloud storage partners, or other methods. 

Your organization must always be aware of newly created or overlooked data in order to keep it protected. AI-driven monitoring introduces a new way to identify data wherever it may be, whether it’s on a standalone in-house system or a massive mainframe.

Enhanced Efficiency

Manually discovering and classifying data is no longer a feasible solution. Even if you use some automated systems but still primarily rely on your workforce, your teams will quickly fall behind.

Autonomous data discovery and classification tools work in the background, making sure every byte of data in your environment is found and able to be protected accurately and operating primarily in the background, requiring minimal human intervention.

Instead of trying to classify data, teams can bolster security practices, ensure evolving compliance requirements are met, and ultimately boost operational efficiency. 

Adopt Inventa for Autonomous Mainframe Data Discovery and Classification

Data discovery is a critical aspect of modern businesses to remain compliant with data privacy and protection regulations while also safeguarding sensitive data against cyber attackers. Without data discovery, data can remain hidden, improperly protected, and at risk of non-compliance penalties.

Mainframes create a unique data discovery challenge due to the data sets they often use that are inaccessible to many tools, unless they specifically leverage the VSAM access method. 

That’s why 1touch has continually enhanced Inventa, with our latest upgrade allowing Inventa to access VSAM data sets to keep your entire data estate classified and protected. 

Are you ready to upgrade your mainframe data management practices? Talk to our data classification experts today to learn more about how our platform helps keep you secure and compliant.