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Today’s hybrid IT infrastructures make it more challenging than ever to identify and protect sensitive data. This data dispersal opens up a wider surface for issues such as data leakage and theft.

Big data security is a multi-faceted challenge for companies that operate in the cloud. This challenging threat includes the theft of information stored online, ransomware, or DDoS attack.

With the amount of information that is shared online, businesses must take steps to protect their customers' data. Data privacy is the process of ensuring that personal information is kept confidential and secure. Data security, on the other hand, is the process of protecting data from unauthorized access or theft.

Data supply chains face many cybersecurity threats. Bearing in mind that businesses often put the data they gather to use by feeding it into various software applications, flaws in those applications can put important data at risk of breach.

Data quality and data integrity are 2 of the most used terms to describe the condition of the collected data. Organizations use these 2 terms to describe the data's accuracy, context, and consistency before using it for decision-making.

What are the vulnerabilities that lead to access control attacks? And how can your team mitigate them before they become a major issue on your customers' trust, business reputation, and bottom line?

As sensitive business data increasingly gets stored in a distributed, multi-cloud infrastructure, the attack surface for threat actors to exfiltrate this data and use double-extortion ransomware increases.

Data sovereignty and data residency are often confusing for businesses managing data across borders, especially with the rise in cloud infrastructure, multi-cloud, and hybrid.

Keeping data under lock and key might sound like a simple task - but in reality, many businesses leave sensitive information under the misconception that it is safe. For many, it is a major challenge.

Keeping track of sensitive data flows in this multi-cloud world makes it challenging to comply with regulations and protect valuable information from prying eyes. ‍

In the past decade, there has been a dramatic increase in the use of cloud services across companies. This increase has made it harder for security teams to fully understand where and what data exists when so many applications and third parties exist.

This article describes the best practices that SaaS manufacturers and their cloud vendors should follow to galvanize this rapidly expanding area of enterprise software delivery.

Whether you’re a CISO, part of a corporate legal department, or you’re involved with DevOps projects that use or create sensitive code and information, here are six steps to safeguard sensitive data. 

Data flow mapping is a technique used to identify the interaction points between all parties in an organization. It tracks the flow of data within the company, including the personal information of the customers, staff, and other third parties involved.

Customer data and other sensitive information are the most important assets that any organization could have, and the organization's responsibility is to keep all attackers away from their crown jewels.

Cloud-native breaches can occur when errors creep into how organizations configure and use cloud infrastructure. Threat actors can exploit such errors and eventually exfiltrate sensitive data from IaaS environments. 

Data security podcasts provide an easy way for professionals to keep up to date with all the changes happening in the security world. This post will look at the best podcasts focusing on data security.

Data protection solutions, and in particular, Data Security Posture Management (DSPM) platforms, should be built to effectively map, monitor, and protect your organization’s most valuable asset — your data.

In today's world of rapid technology advancement, data, and sensitive data in particular, turned into companies' most valuable assets. Here's how to keep it safe.

Automation will directly strengthen your compliance by giving you the ability to automatically detect every compliance issue as it arises and instantly mitigate it.

As more and more organizations move to the cloud and as the technology becomes more complex, so do the threats. Protecting your cloud environment and maintaining a strong and efficient posture is essential. Here are 10 best practices to do just that.

A thorough overview of the clear benefits of enabling a cloud data protection platform within your organization and how to do so with ease.

While DLP provides value in certain cases, it does not solve the fundamental problem cloud organizations are facing – how to keep data secure in the real world, where data is being created at light speed.

In this blog post we will cover the basics of Data Subject Access Request (DSAR) and why companies need to pay close attention to this compliance subject matter.

In this post we will review 10 data vulnerabilities that can cause data loss, and how to mitigate them.

Preventing data breaches and protecting sensitive data has become one of the highest priorities in any organization. In this post, we’ll discuss what sensitive data is and how to protect it.

How to improve PCI compliance - reviewing the top 12 PCI compliance solutions on the market.

We're excited to announce that we are now compliant with the System and Organization Controls (SOC) 2 Type II standard for security, availability, and confidentiality.

Join us as we uncover the main differences between structured and unstructured data, in a world of modern data complexity.

Data protection, once a marginalized subsection of the cybersecurity industry, has increasingly become a major concern, especially for companies deploying Cloud based applications. GDPR, CCPA, PIPEDA - The list goes on but they all have one thing in common - A focus by regulators worldwide on addressing the issues presented by the use of digital big data.

Shadow data can be defined as any data that is not available or subject to an organization’s centralized data management framework. Examples of shadow data include:..