How Data Security can Safeguard Big Data-Driven Businesses

Apac CIO Outlook | Wednesday, September 01, 2021

Structured and unstructured data repositories, such as databases, big data platforms, data warehouses, and cloud environments can contain sensitive data. Data discovery and categorization software automate the process of identifying sensitive data, as well as assessing and resolving security flaws.

FREMONT, CA: Because of digital transformation, the way firms operate and compete is always changing. Companies are creating, collecting, controlling, and storing more data than ever before, necessitating a higher need for data security and governance. Furthermore, computing technologies are evolving and becoming more crucial than they were previously, resulting in a plethora of edge devices such as IoT sensors, remote servers, robotics, and big data.

Large data is at the heart of digitized scenarios, and data security is critical for managing and controlling big data. Data security has become more important, especially for essential industries dealing with huge data, as a result of the increasing number of cyber-attacks that occur primarily in the age of modern digital technology. If an industry's big data is breached, the entire business system will be brought to a halt.

Here are some data security tools that can prevent big data-driven businesses:

Data Discovery and Classification Tools

Risk Analysis Tools

This solution simplifies the process of detecting and resolving vulnerabilities such as out-of-date software, misconfigurations, and weak passwords, as well as detecting data sources that are at high risk of being exposed.

Monitoring Data and File Activity

Security teams can use file activity monitoring technologies to see who is accessing data, spot anomalies, and assess threats by analyzing data usage trends. For inappropriate activity patterns, dynamic blocking and alerting might be used.

See Also: Top Big Data Solution Companies