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What is Structured Data?

Structured data is highly organized information stored in databases, typically in rows and columns, making it easily searchable and analyzable. It includes financial records, customer databases, and inventory management systems.

Data Management
Data management encompasses the practices, policies, and technologies used to collect, store, process, and secure data throughout its lifecycle. It ensures data quality, accessibility, and compliance, supporting decision-making and business operations. Data management includes aspects such as data governance, security, and metadata management.
Anomaly Detection
Anomaly detection is the process of identifying patterns in data that deviate significantly from the norm. It leverages machine learning and statistical techniques to detect unusual behavior, making it essential for applications such as fraud detection, cybersecurity, manufacturing quality control, and healthcare analytics. The two primary approaches to anomaly detection are supervised learning (using labeled data) and unsupervised learning (detecting anomalies without predefined labels). AI-powered anomaly detection is particularly effective for processing large-scale, real-time data, ensuring data integrity, security, and operational efficiency.
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.