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How Does Data Visibility Help With Data Loss Prevention?
What Is Data Visibility And How Does It Help With Data Loss Prevention?
Data loss prevention starts with data visibility. Without a clear idea of what data an organization has, where it lives, and how it’s used, data loss prevention (DLP) is essentially an exercise in futility.
While the concept of data visibility may seem straightforward, in practice, it’s a challenge. The rise of remote work has led to a proliferation of devices and programs that prevent an IT team from getting a clear picture of where data lives. Nevertheless, data visibility is imperative for companies that want to stay compliant and keep valuable information secure. And, data visibility can provide a competitive business advantage to those who achieve it.
What is data visibility?
Data visibility is the ability of an organization to monitor, display, and analyze data in use, data in motion, and data at rest. Essentially, data visibility answers the question: how easy is it to monitor and manage data across devices and systems owned by the enterprise?
Data visibility has a number of security and business benefits. Organizations with strong data visibility are able to capture customer insights, find ways of working more efficiently, and optimize spending. Likewise, organizations with high data visibility can implement security controls and proactively manage user permissions to ensure valuable information is protected.
Data visibility may seem like a simple concept, but it can be difficult to achieve high data visibility.
Common data visibility challenges
Data visibility is made difficult by the proliferation of devices to assist with remote work, the rise of shadow IT, and by user behaviors that create siloes in the organization.
Consider this: 14% of employees use six or more corporate-issued or approved tech devices. Most employees use two or more devices, according to global surveys by Forrester. At a company with just 50 employees, that’s more than 100 devices on which valuable information can be shared and stored.
When you add in servers, shared networks, databases, and cloud programs, the list of locations where sensitive information could exist grows exponentially. Today, it’s estimated that the average company has 254 SaaS apps; and, on average, only 45% of company apps are being used on a regular basis. Maintained lists of places where sensitive data is stored could potentially miss dozens of apps — leaving data unprotected and at risk.
Shadow IT presents a data visibility challenge for many IT teams. More than 50% of all apps are “shadow IT”, applications owned and managed outside of the IT team’s approval. An employee who uses their company email on a personal device is an extremely common example of shadow IT. And, since you can’t protect what you can’t see, the use of shadow IT leaves company data vulnerable.
Finally, some user behavior can also make it difficult to gain data visibility. When organizations don’t implement version control best practices, or use tools that make it easy to collaborate, users often hold versions of documents unique to their workstations. Imagine the same document, saved on every person’s desktop, containing the same information.
“At any given time, you’ll have storage space wastage due to there being redundant data on the network,” wrote one expert.
Solving this issue of data visibility means breaking down siloes with cloud programs, implementing naming conventions, and using a program to automatically scan for data vulnerabilities rather than manually checking duplicates.
Benefits of data visibility
The benefits of data visibility apply both to the productivity and the security of the organization.
First, the business benefits: a company with high data visibility can access deeper insights that can help understand customers, optimize operations, and save money. When a company can easily find and use data from its sales team, customer service center, marketing reports, and other sources, then it can turn that data into action. Data can be used to improve everything from product pricing to supply chain management to marketing messaging.
It can also improve internal operations. High data visibility enables IT teams to troubleshoot network performance problems or application downtime. Data visibility also helps the team proactively manage user access and permissions; when a partner or employee requests access, the team immediately can see whether the request is appropriate given the information and make a decision to approve or deny the request.
From a security perspective, data visibility empowers the enterprise to immediately identify sensitive data, classify, and protect it. Data visibility is critical for data loss prevention.
Why is data visibility important for data loss prevention?
Data loss prevention is predicated on knowing where data is stored, shared, and used. Cloud DLP tools discover, classify, and protect an organization’s most sensitive data in SaaS, PaaS, and IaaS platforms, using data visibility to provide an additional layer of protection without draining the resources of the IT team.
Nightfall, a cloud DLP program, uses AI to efficiently discover, classify, and protect data by integrating directly with popular cloud platforms like Salesforce, Slack, Jira, Confluence, Github, Google Drive, and more on the API level.
Once installed, Nightfall automatically scans both structured and unstructured data, with the capability to parse text from 100+ file types, including customer chat logs, JSON objects, application logs, spreadsheets, PDFs, images, screenshots, and more. This provides visibility into areas in which IT teams may not even think to look — or have the resources to monitor regularly.
Nightfall makes it easy to customize and configure detections for the data you wish to protect. Nightfall customers are typically up and running within a few minutes. For SaaS apps, there’s no additional configuration or setup required beyond installation — though developers also gain the ability to build their own integrations as needed.
Gain greater data visibility with Nightfall. To get started, schedule a demo at the link below.
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Nightfall is the industry’s first cloud-native DLP platform that discovers, classifies, and protects data via machine learning. Nightfall is designed to work with popular SaaS applications like Slack, Google Drive, GitHub, Confluence, Jira, and many more via our Developer Platform. You can schedule a demo with us below to see the Nightfall platform in action.
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Select a time that works for you below for 30 minutes. Once confirmed, you’ll receive a calendar invite with a Zoom link. If you don’t see a suitable time, please reach out to us via email at firstname.lastname@example.org.