What is data protection governance?

Data protection governance can best be described as a structured approach organizations can adopt to ensure all their sensitive data is collected, stored, used, shared, and secured in a manner compliant with their relevant regulatory obligations by leveraging the best data security practices. This involves several processes being undertaken simultaneously, such as defining policies, procedures, and controls that mitigate unauthorized access, loss, or data abuse.

Is data governance cybersecurity?

While it may seem like data governance is part of an organization's cybersecurity considerations at first, they are related but thoroughly distinct concepts. Cybersecurity involves all considerations and steps taken to protect an organization's internal networks, systems, and hardware from all manner of cybersecurity threats, such as hacking, malware, DDoS, and other such attacks. On the other hand, data governance focuses on managing data itself, such as ensuring its quality, accuracy, consistency, and integrity with appropriate mechanisms in place to do so.

What is a data security governance framework?

A data security governance framework is a set of policies, controls, and best practices designed to ensure an organization's data resources' appropriate quality, availability, and integrity. Under such a framework, organizations can define roles and responsibilities for their personnel, devise data security policies, and implement measures necessary to ensure compliance with regulatory requirements and risk management considerations. Some examples of such frameworks include ISO 27001, NIST Cybersecurity Framework, and CIS Controls.

Is data governance the same as data stewardship?

While they may be closely related as concepts, they are operationally different. Data governance focuses on developing appropriate policies, procedures, and practices for managing data across organizations. Data stewardship involves the enforcement of these policies, procedures, and practices across the organization. In other words, data governance is the "what" and "why" of data management, while data stewardship is the "how", making them both equally important and relevant for organizations' effective data management.

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Syeda Eimaan Gardezi

Associate Data Privacy Analyst at Securiti

Syeda Eimaan Gardezi is a CIPP/A certified lawyer. She graduated with distinction and holds a BA-LL.B (Hons) degree from Lahore University of Management Sciences. Passionate about the intersection of law and technology, she continuously expands her expertise to help organizations navigate the complexities of privacy, security, and ethical AI practices.

At Securiti, her role involves researching data and AI laws, creating privacy assessments, and developing strategies for data subject rights and breach management. She also supports consent management, and business development efforts.

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Secure sensitive data everywhere from hybrid multicloud to SaaS

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Establish controls for safe adoption of AI technologies including GenAI

View

Security for AI Copilots in SaaS
Unblock the biggest impediments for Safe Adoption of AI Copilots like Microsoft 365 Copilot

View

Data Access Intelligence & Governance
Monitor user access to data and enforce least privilege controls

View

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Compliance Management
Assess & improve compliance with security best practices frameworks

View

Breach Impact Analysis
Analyze breach impact & automate notifications to affected individuals

View

Data Flow Governance
Understand data lineage and secure real-time streaming data

View
Build safe enterprise AI systems

Safe Enterprise AI Copilots
Implement rule-aware AI copilots across your organization’s data anywhere

View

Data Vectorization and Ingestion
Extract info from complex Unstructured Files, convert it into AI-ready formats, and sync to vector databases

View

Data Curation and Sanitization for AI
Transform raw, unstructured files into data ready for model training and tuning

View

Context-aware LLM Firewalls
Protect AI interactions with intelligent retrieval, response, and prompt firewalls

View

Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

View
Govern data for safe innovation

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Unstructured Data Governance
Manage unstructured data to enable safe use with generative AI

View

Data Access Governance
Monitor sensitive data access and prevent unauthorized use

View

AI Governance
Establish controls for safe adoption of AI technologies including GenAI

View

Data Catalog
Enable users to easily find, understand, trust and access the data they need

View

Data Lineage
Automatically track changes and transformations of data throughout its lifecycle

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Data Quality
Conduct data quality checks and validation across various data types

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Automate data privacy operations

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Manage your entire data mapping lifecycle and automate RoPA reports

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Comply with emerging AI regulations and ensure safe use of AI

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Automate your incident management and optimize notifications to users & regulatory bodies

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