How to Improve Your Big Data Security Processes

Data Security
Best Practices
5 min read
James Mignacca
July 14, 2022
James Mignacca
July 14, 2022
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Big Data Security Issues—and 10 Best Practice Frameworks to Help Mitigate Them
This blog reviews primary data security risks associated with big data and the recommended frameworks companies can apply to safeguard big data.

Big data has become a common term in recent years, often referring to large volumes of both structured and unstructured data that is difficult to manage and can easily become a day-to-day challenge for organizations that don’t get a handle on it.

In fact, big data is so important that 97.2 percent of organizations say they are now investing in artificial intelligence (AI) and big data. Yet, despite this, around 95 percent of companies say their inability to understand and manage unstructured data is holding them back.

When stored, used and managed correctly, big data is an important tool that allows businesses to gain crucial insights into people, processes and business performance.

Yet, when handled incorrectly, big data can be both a data protection and data compliance concern.

Maximizing Big Data Security

So, how can your organization improve its big data processes so that you can mitigate your data protection and compliance risks? In this blog, we discuss the top five ways your business can improve its data security processes.

1) Gain visibility into where your data lives, how it’s being used and who has access to it

To mitigate the data protection and compliance risks associated with big data, data visibility is crucial. To achieve this, businesses need to implement an effective data discovery platform that scans their entire environment to find and identify where both structured and unstructured data resides.

A data discovery platform allows businesses to gain visibility into where their data lives, how it’s being stored, how it is being used and which employees within the organization have access to it. By gaining visibility into their data, businesses can ensure that they are appropriately protecting vulnerable data and complying with the data privacy regulations that apply to their business.

To go one step further, data discovery should be combined with data classification. By classifying data, organizations are able to seamlessly tag data based on its content and how it needs to be handled. These tags make it easier for companies to locate and retrieve data as well as ensure all data types are complying with the appropriate data privacy regulations.

2) Provide data security training and best practices to employees

Unfortunately, the vast majority of data breaches are due to human error. In fact, according to CISCO’s 2021 Cybersecurity Threat Trends report, at least one person clicked a phishing link in around 86 percent of organizations. The company estimated that phishing accounts for around 90 percent of all data breaches.

To mitigate these vulnerabilities and minimize the risk of successful cyber attacks on employees, it’s crucial that you implement employee training and best practice policies into your company’s big data security processes. Training your team to know what phishing attempts are and what they look like, as well as the best practices that can help them avoid falling prey to cyber criminals.

3) Encrypt personally identifiable information

Personally identifiable information (PII) should be encrypted in transit and at rest to further protect your organization’s sensitive data from unauthorized access. Encryption can help your business secure a massive volume of data of different data types, and data can be encrypted either via machine or through a user-generated code.

4) Limit who has access to sensitive data

Employees should only ever have access to sensitive data if it’s crucial to their job. That’s because the more people that have access to data, the more that data is vulnerable to external threats. This is where data visibility is key.

A data discovery platform can help your business visibility over where your data lives and which employees have access to it. You can then use those insights to limit data access permissions to the employees that truly need to access that data as part of their job role.

5) Implement an intrusion detection and prevention system

Since there’s a large amount of sensitive information, big data is a particular focus for intrusion attempts. To better protect this data, organizations should ensure they implement an intrusion detection and prevention system.

An intrusion detection system is a software that monitors a company’s network or system for malicious activity or policy violations. If an intrusion or violation is found, an intrusion detection system can automatically report this to an administrator. If an intrusion is detected and is successful, the system can typically stop the intrusion before it does significant damage.

Ensure Big Data Security with Cavelo

This is also a service provided through Managed Security Service Providers (MSSPs) through their broader Security Operations Center (SOC) services. Are you interested in learning more about how your business can improve its big data security processes?

Get a demo of the Cavelo attack surface management platform today. We simplify your data protection policies through seamless asset discovery, classification and risk management.

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