Unlock Your Sensitive Data by First Understanding the Data You Have

April 6, 2021
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A business can’t manage or protect data it doesn’t know it has.

Much like losing your keys in a messy house, data can easily get lost in on-premises systems. Getting a handle on data in a modern enterprise that relies on hybrid-cloud infrastructure is even more difficult; it’s like losing track of thousands of keys in hundreds of houses.

That’s because data is everywhere. For most organizations, data is spread over an array of locations: data warehouses, analytics systems, mainframes, and file servers, across on-premises systems, in cloud infrastructures, and in hybrid-cloud environments. Gathering and corralling all of that data—and then securing it so that it can be used to gain valuable insights—is a challenge that won’t get easier any time soon.

IDC predicts that by 2025, 175 zettabytes (or 175 trillion gigabytes) of new data will have been created around the world. Add to that the many zettabytes that have been annually produced over the past decade, and you have a lot of data—much of which is sensitive. With governments increasing regulatory oversight of data—and with individuals demanding their data be kept private—organizations have some big hurdles to clear before they can boast of protecting all of their data.

These are hurdles that can be surmounted, however, with practice and due diligence. The first order of business is to determine what kind of data your organization possesses, figuring out which of that data is considered sensitive, and then learning where that data is. That’s what the research firm Forrester recommends in its report, “A Five-step Strategy for Data Discovery and Classification.”

The Fundamental Questions

Organizations must first ask and answer those three fundamental questions before embarking on critical discovery and classification work that allows the data to be harnessed, protected, used as a key source of innovation and business growth.

Defining data through data discovery and classification, Forrester says, creates a foundation to better understand data’s useful lifecycle. The data lifecycle spans from creation or collection,

to processing and use, through retention and destruction. Understanding data’s true value and the risk it poses as it runs through the lifecycle will put companies in the best position to protect it. As Forrester points out, the personal information of a customer who last placed an order five years might no longer be an asset but rather a liability if it’s not properly managed.  

Businesses need to understand which data needs protection and how it should be protected. Not all data is sensitive, and not even all sensitive data requires the same level of protection.

Again, the data race is won with preparation. When your organization discovers and classifies data without difficulty you can confidently clear the many hurdles that make data protection difficult. In the end, it all comes down to business benefits—including operational efficiency, agility, and innovation—from prioritizing data privacy.  And for that we have a white paper from which you can find out more about new approaches to a data-driven business.