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Data security posture management (DSPM) is an emerging market focused on reducing risk and improving the security around an organization's most valuable asset: its data. DSPM can help organizations automatically understand the data they have across their tech stack while reducing their risk for data breaches, leaks, compliance violations, audits and more.

With data growing faster and in more places every day, cloud DSPM has become a top concern for security professionals.

Since DSPM is becoming a critical market to address data security, let's take a look at the critical capabilities required for data security posture management and what you need in order to assess your risks in cloud data protection and compliance.

Know your data.

If you don't know where your sensitive data is, how can you take steps to protect it? The first step in protecting your data is to understand what data you're storing in the cloud in the first place.

• Discover where all of your data is stored throughout different data sources in the cloud across SaaS, IaaS and PaaS.

• Identify what type of data you have in order to reduce dark and unknown data—structured databases, files, images, documents and more.

• Classify all of your data to give accurate context to the data found, and categorize sensitive data—passwords, Social Security numbers, dates of birth, etc.

• Build an accurate data inventory to gain visibility in a unified view—what data you have, who it belongs to, how important it is and where it is stored.

Prioritize your data.

After you discover and classify all of your data, it's more important than ever to prioritize data security for highly valuable and highly sensitive data. It can be noisy out there, so your security teams need to know the hot spots to address first.

Different types of data require different security controls, handling methods and urgency. You wouldn't treat car model information the same as Social Security number information.

• Determine what data you have that is considered sensitive—crown jewel data, personal information (PI), security access tokens, ID numbers, etc.

• Determine what data you have that is regulated by policies—whether that's payment card information (PCI), protected health information (PHI), financial data or more.

• Define and evaluate risk level distribution across your data catalog based on sensitivity, risk and regulations.

• Identify areas of focus for data protection based on the amount and the level of sensitive and regulated data contained.

Minimize your attack surface.

Data minimization helps to reduce your attack surface so those with malicious intent have less data to target, making it more difficult for them to find the sensitive data they're looking for. Protecting cloud data and staying compliant becomes a faster and simpler process, saving you time and resources.

• Limit the collection of data to only what is relevant and necessary to achieve your purpose.

• Pinpoint what sensitive data you have, where it is located and how it is being used and accessed to find problem areas in data security.

• Retain any data for only as long as you need it, and discard unused data.

• Identify and delete duplicate and similar data to maintain a clean data environment.

Monitor your data.

It's not only enough to have a current inventory of all of your data, but it also must be maintained and kept up to date. New data is created every day, and old data is constantly being modified, so it's important to have a system in place to keep track of these changes.

• Keep a current inventory of your data and schedule scans to monitor for changes and new data.

• Update your data inventory dynamically based on changes through automation.

• Create automated policies to monitor 24/7 for potential violations in security and compliance.

• Review policy findings and proactively act on them to stop breaches and noncompliance before they happen.

Get a head start on data security posture management.

The massive migration of data to the cloud has made cloud DSPM a top priority for security professionals. An organization's data security strategy should offer high accuracy in data discovery and classification, fast time-to-value and flexibility in scale based on their data.

Finding the right approach to reduce risk and improve security posture can be tricky. To get a head start, look for the following minimum capabilities.

• Native coverage for data sources across cloud and on-prem for a centralized data inventory.

• Modern techniques and machine learning to scan data faster across structured data, unstructured data and data-in-motion.

• Advanced classification for accurate context and fewer false positives.

• Out-of-the-box and customizable classifiers and policies to align with security frameworks and regulations.

• Policy management and workflows to monitor data and investigate findings.

As the world continues to run on data, it's more critical to take a data-centric approach that is able to evolve with the data—not in spite of it.

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