We use cookies to ensure that you have the best experience on our site.

What is Data Anonymization?

Data anonymization is the process of modifying personal or sensitive data to remove or mask identifying information, ensuring privacy and compliance with regulations like GDPR and HIPAA. Techniques include data masking, tokenization, and synthetic data generation, making it crucial in AI training, healthcare analytics, and cybersecurity.

Big Data Analytics
Big data analytics involves examining large and complex datasets to uncover patterns, correlations, and insights. It utilizes machine learning, statistical methods, and data visualization techniques to drive informed decision-making across industries.
External Data Representation
External Data Representation (XDR) is a standard for encoding and decoding structured data to enable interoperability between different computing systems. It ensures data consistency across platforms by converting data into a platform-independent format. XDR is commonly used in distributed computing and network protocols to facilitate seamless data exchange between heterogeneous systems.
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is an AI technique that enhances text generation models by retrieving relevant information from external sources before generating responses. This approach improves the accuracy, relevance, and contextual awareness of AI-generated content. RAG is widely used in knowledge-based AI applications, including chatbots, search engines, and automated research tools.