Elena Canorea
Communications Lead
A company’s data is one of its most valuable assets. Whether gaining insight into customer opinions, monitoring market trends, or maintaining its competitive edge, data is crucial to a good business strategy.
However, the immense volume of data that companies generate today means that the threat landscape is also growing, and data protection is becoming more complicated. That’s why approaches such as DLP are essential to protecting sensitive data and the people who handle it. We review what DLP is, how it works, and the reasons why you should implement it in your company as soon as possible.
Data Loss Prevention (DLP) refers to a cybersecurity solution that detects and prevents data breaches. By blocking the extraction of sensitive data, organizations use it for internal security and regulatory compliance.
DLP enables companies to detect data loss, as well as prevent the illicit transfer of data outside the organization and the unwanted destruction of sensitive or personally identifiable data (PII). It also helps organizations with compliance with various local and national regulations.
Its main advantages are:
Data threats are actions that can affect the integrity, confidentiality, or availability of the organization’s data, while data breaches expose sensitive data to untrusted environments.
The most common threats are:
DLP is a multi-step process that relies on a coordinated effort among several components. Each step plays an important role in the success of the solution in protecting an organization’s valuable data.
A DLP solution for today’s distributed organizations requires AI and ML-based classification to help with pre-discovery and classification.
An organization’s data can be classified into 3 general categories:
In many cases, a combination of the basic methods is used to ensure proper classification of the data:
Data protection solutions should include policy packages that simplify the creation of policies for different compliance requirements and rules on how different classes of data should be handled.
With DLP solutions, the process of enforcing these data handling policies and resolving any issues that arise is automated. This may involve encrypting data before allowing it to be transferred or applying a different policy for business or personal accounts.
These types of solutions should generate reports and analytical information that can be used to optimize data management policies and address a company’s operational gaps and vulnerabilities.
These analytics can identify the applications that make the most use of high-risk data and can influence how cybersecurity is implemented throughout the organization. As a result, companies must rely on techniques to prevent data loss.
All members of the organization, regardless of department, must be informed about the risks involved in insecure data handling.
End users must understand how they can use data without introducing risk to the company. Regular participation in cybersecurity awareness training courses is therefore very important. This will reduce the likelihood of accidentally exposing confidential or sensitive data that could damage the company and its reputation.
Organizations handle more sensitive data than ever before, so security and privacy have become a top concern for businesses. In fact, according to IBM’s Cost of Data Breach Report, compliance failures were one of the three factors associated with the largest net increase in the average cost of a data breach.
So, with increasing pressure to comply with these regulations and rules, organizations are finding themselves with a great need to implement a modern DLP solution that provides immediate value and flexibility to adapt to changing regulations.
In addition, DLP solutions are especially useful when dealing with multinationals, where data management by employees must be facilitated in an uneven regulatory landscape.
If an organization is trying to mature in the field of data protection, implementing a DLP solution will be the best option because, by being context-aware, it enables the automatic collection of information about the use and movement of data in and out of the enterprise, providing the organization with valuable insight and visibility into its data and preventing costly breaches.
With constant data threats, it is important to consider when they will occur, not if they will occur. Choosing a DLP solution for your organization requires research and planning. This investment of money and time will ensure that your sensitive data, personal information, and company reputation are protected.
Knowing the different options and how they work with DLP can help you get started on the road to a safer and more secure data environment:
At Plain Concepts we offer you customized governance, protection, and compliance solutions for your organization with Microsoft Purview and our Zero Trust strategy. Moving to a Zero Trust security model doesn’t have to be all or nothing. We recommend using phased approaches, closing the most exploitable vulnerabilities first, covering identity, endpoints, applications, networks, infrastructure, and data.
In addition, we are specialists in unlocking the potential of technology and solving our client’s challenges by applying the latest techniques available. Whether you are unfamiliar with AI or generative AI, don’t know how to apply it, or already know what you want, we can help you accelerate your journey through artificial intelligence with the best experts in the field.
We will analyze where your data is at, explore the use cases that best align with your goals, create a custom plan, create the patterns, processes, and teams you need, and implement an AI solution that is secure, modern, and meets all compliance and governance standards:
Don’t wait any longer to protect and secure your data!
Elena Canorea
Communications Lead
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