By Eldad Chai, CEO & Co-founder, Satori Cyber

Today's organizations run on data. It is the fuel that companies use to make strategic business decisions, better connect with customers, and create new revenue streams. Data comes from a variety of sources - both third-party and proprietary - and proactively managing data access and security is important to building trust and preventing misuse.

Similarly, data compliance cannot be an afterthought. To adhere to mandates and provide audit trails, compliance leaders need visibility into where sensitive data is stored, who is accessing it, and when it is updated or deleted. However, the default process is daunting. 

First, they must ask data engineers and platform owners for the given data store to extract logs. Then, a report must be compiled manually for compliance with various consumer data protection laws, including state-wide legislations such as California Consumer Protection Act (CCPA) and Virginia Consumer Data Protection Act (CDPA), and international laws such as the EU General Data Protection Regulation (GDPR) and China's Personal Information Protection Law (PIPL). 

This process takes too much time, involves too many resources, and is plagued with errors. By adopting modern data governance strategies and principles known as Data Security Operations (DataSecOps), compliance leaders can overcome these challenges and reduce risks involved in handling sensitive data. 

Compliance Challenges for Data-Driven Companies

Organizations face three inherent challenges when trying to ensure compliance in an increasingly data-driven business world: discovering sensitive data, controlling access to sensitive data, and reporting and auditing access to sensitive data. 

Challenge #1: So Much Sensitive Data (and Too Little Visibility)

The amount of data used, generated, stored, analyzed, and shared on the cloud continues to grow.  Organizations need to continuously discover and monitor all data usage to identify compliance risks. Real-time visibility about who is accessing the data and why, and automatic identification and classification of sensitive data such as PII, PHI, and PCI, is critical to ensure data compliance.

Challenge #2: So Many Regulations (and Lack of Control)

With the constantly evolving regulatory environment and the requirement to comply with GDPR, CCPA, and other data privacy and security mandates, it's important that organizations have specific controls in place. By automatically detecting sensitive data, controls can be set up to ensure data integrity and provide secure, need-to-know access. Enforcing data access controls will alleviate any concern that data is getting into the wrong hands. It also creates the necessary monitoring and audit trail for compliance reporting.

Challenge #3: So Much Complication (for Reporting & Auditing)

To better comply with privacy laws and regulations, organizations should implement universal auditing and reporting capabilities for sensitive data. By automatically locating sensitive data in data stores and monitoring its usage, compliance teams can easily generate reports listing all instances of PII, PHI, and PCI data. Data access patterns can also be mapped and analyzed, providing a simple way to conduct risk assessments based on the data's class, accessibility, and volume.

Data-driven organizations can overhaul their data compliance approach to conquer these difficulties. Traditionally, data identification, access control, and reporting has been done manually. It is slow, reactive, and does not provide a complete picture of an organization's compliance position. DataSecOps is a modern approach that powers secure data access while gaining complete visibility over how sensitive data is used throughout the enterprise.

Discover, Enforce, Automate 

To remain compliant and secure, companies need to govern access to their sensitive data. However, when data is spread across multiple locations and data platforms are accessed by multiple teams, this becomes a complicated task.

DataSecOps helps data-driven companies simplify compliance by following three core principles: discover, enforce, and automate.

Discover and Classify Sensitive Data Continuously: It's time for companies to put aside cumbersome data mapping projects and implement DataSecOps to continuously discover and classify sensitive data (including PII, PHI, and financial data including PCI), and mask it at query run-time. DataSecOps controls access to sensitive data based on role and attributes, and automatically produces compliance reports with a complete audit trail.

Enforce Data Security Without Business Disruption: Substantial engineering resources are usually required to enforce security policies and compliance guidelines. This can delay data, security, or compliance projects. DataSecOps identifies users who access data in a non-compliant manner, automatically alerts of data security requests for sensitive data, and implements new controls without disrupting global data teams' day-to-day work. 

Automate Data Access Policies: DataSecOps streamlines and automates data access policies, including fine-grained data access controls, approval workflows, and self-service access to data. With these capabilities, organizations can set their policies on "autopilot" and free up resources to concentrate on minimizing risks.

DataSecOps is the key to confident compliance. This modern approach to data security relieves compliance managers of relying on manual analysis of database logs and ad-hoc compilation of reports, and enables regulatory compliance reporting by continuously discovering and classifying sensitive data. 

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ABOUT THE AUTHOR

Eldad Chai is the Co-Founder and Chief Executive Officer of Satori Cyber. Satori is the developer of the first DataSecOps platform - a universal data access platform for cloud-based data stores and infrastructure - and winner of four 2022 Cybersecurity Excellence Awards. Prior to founding Satori Cyber, Eldad was a senior executive at Imperva.