India's Digital Personal Data Protection (DPDP) law, enacted in 2023, represents a pivotal step in safeguarding personal data privacy while fostering accountability among entities handling such data. As businesses grapple with its requirements, understanding its core mandates, applicability, timeline, and implications is critical for compliance and operational efficiency.

LLMs are based on neural network architectures, with transformers being the dominant framework. Introduced in 2017, transformers use mechanisms called attention mechanisms to understand the relationships between words or tokens in text, making them highly effective at understanding and generating coherent language. Practical Example: GPT (Generative Pre-trained Transformer) models like GPT-4 are structured with billions of parameters that determine how the model processes and generates language.

Cyber insurance underwriters consider a range of variables to assess the risk a company presents and, consequently, determine premiums. These variables can broadly be categorized into organizational factors, security posture, third-party interactions, and incident history.

This collaboration is a significant step forward in making robust data security accessible to all organizations. By leveraging the Azure Marketplace, we're empowering Azure customers to easily discover, deploy, and integrate Riscosity into their existing infrastructure. This seamless integration allows for a streamlined experience and faster time to value.

While Data Security Posture Management (DSPM) is a powerful approach for discovering, monitoring, and managing sensitive data across complex systems, it is not without its challenges. These hurdles often stem from the complexity of modern data environments, evolving threats, and operational constraints. Below are the primary challenges associated with DSPM.