Apr 26, 2024 · This blog post takes a deep dive into data protection from a data warehouse modeling perspective. More precisely, we'll explore modeling principles that enable compliance with regulatory requirements, such as the right to data access or erasure, all while preserving the data model's structural integrity.

May 24, 2018 · Some threat modeling example questions related to data protection are: What is the sensitivity of the data? What are the regulatory, compliance, or privacy requirements for the data? What is the attack vector that a data owner is hoping to mitigate?

privacy protection requirements to the organization’s data assets. This publication defines basic. language for all to use. It can also help organizations improve the quality and efficiency of their. compliance reporting and monitoring, zero-trust architecture, and large language models. protection; data security.

Apr 22, 2025 · UDM Event: Stores data for an action that occurred in the environment. The original event log describes the action as it was recorded by the device, such as firewall and web proxy. This is the...

Cyber IDEAL examines the potential for an unauthorized disclosure and estimates the likely cost per breach. Using US historical breach information dating back to 2005, the model determines the frequency and severity of cyber incidents using a one-year probability of a data-breach event.

May 31, 2024 · This method of taking data to track events in my experience fits large tech companies rather well, both due to the metrics they focus on such as retention, monthly active users, etc as well as the data size they are dealing with.

Feb 16, 2024 · Information security models are essential systems designed to protect data and ensure the smooth operation of underlying systems. These models go beyond theoretical frameworks by offering practical guidelines to control data access and maintain security.

May 25, 2018 · When evaluating the security of an application and data model ask the questions: what is the sensitivity of the data? What are the regulatory, compliance, or privacy requirements for the...

Apr 26, 2024 · Data modeling adds clarity and a unified language to data work and analysis by creating blueprints that help understand data structures and connections. In this article, I make an effort to explain why data modeling is worth it, and how you can implement it on the levels of conceptual, logical, and physical data models. What is data modeling?

Examples of event data include website clickstream data, sensor data from IoT devices, social media posts, and transaction logs. Event data is used for various purposes such as analyzing user behavior, detecting anomalies, predicting trends, and improving business processes.