Enterprise Technology Glossary

6,173 results · page 107 of 309

• Event Simulation Framework

  Event simulation framework is a software environment for modeling and executing time-based events in complex systems under controlled conditions, enabling enterprises to evaluate behavior, capacity, resilience, and risk scenarios using repeatable simulations and structured performance, reliability, or policy analyses.

• Event Sourcing

  Event sourcing is a software design pattern that stores all application state changes as an append-only sequence of events, which enterprises use as a system-of-record log to support auditability, traceability, replayable state reconstruction, and analytics across complex transactional domains.

• Event Stream

  Event stream is a continuous, ordered flow of event records emitted by systems or devices and delivered over a data pipeline for real-time use, enabling enterprises to distribute, observe, and process operational data across applications and analytics platforms.

• Event Streaming Platform

  Event streaming platform is a software system that captures and distributes continuous event data as ordered streams in near real time, providing durable storage, replay, and integration capabilities that support enterprise analytics, event-driven applications, and data-in-motion architectures.

• Event Stream Processing

  Event stream processing is a data processing paradigm and software architecture style that continuously ingests and analyzes event data in motion with low latency, enabling enterprises to perform real-time monitoring, analytics, and automated responses within event-driven and data platform environments.

• Event Stream Processor

  Event stream processor is a software capability that processes continuous event data streams in near real time, enabling enterprises to apply rules and analytics as data arrives and to route derived results into monitoring, security, and operational systems.

• Event Stream Validation

  Event stream validation is the programmatic verification of continuous event data against defined schemas, quality rules, and policies in streaming architectures, which helps enterprises maintain reliable real-time pipelines, enforce data contracts, and support governance and operational control over event-driven systems.

• Event Telemetry Stream

  Event telemetry stream is a continuous flow of time-ordered machine-generated event data from systems, applications, networks, or devices that enterprises use for monitoring, observability, security operations, and analytics across on-premises, cloud, and hybrid environments.

• Event Time Windowing

  Event time windowing is a stream processing technique that groups events by the time they actually occurred, as recorded in event timestamps, enabling enterprises to compute accurate time-based metrics and analytics even when data arrives late or out of order.

• Event-Triggered Workflow

  Event-triggered workflow is an automated sequence of tasks that initiates when a defined event occurs in an application, system, or data platform. It matters in enterprises because it coordinates real-time, policy-based responses across distributed services, integrations, and business processes.

• Evidence Collection

  Evidence collection is the structured process of identifying, acquiring, preserving, and documenting digital or physical artifacts so organizations can investigate incidents, support audits, meet regulatory obligations, and present reliable, verifiable information in internal reviews or external legal and compliance contexts.

• Evolved Packet Core

  Evolved Packet Core (EPC) is the 3GPP-defined all-IP core network architecture for 4G LTE that manages data transport, mobility, policy, and charging, and enables interworking between LTE access, other radio technologies, and external IP networks in operator and enterprise environments.

• E-Waste Recycling

  E-waste recycling is the controlled processing of discarded electrical and electronic equipment to recover reusable materials and manage hazardous components under regulatory and environmental standards, which supports enterprise asset disposition, compliance, and documented hardware lifecycle management.

• Exabits Per Second

  Exabits per second (Ebps) is a data transfer rate unit equal to 10^18 bits per second, used to describe very large-scale throughput in digital networks and computing infrastructure, including aggregate capacity planning for backbones, data centers, and high-performance environments.

• exascale

  Exascale is a high performance computing capability defined by systems that achieve at least one exaflop, or 10^18 double-precision floating-point operations per second, enabling large-scale simulation and analytics workloads relevant to scientific research, engineering, and data-intensive enterprise use cases.

• Exascale AI Integration

  Exascale AI integration is the coordination of artificial intelligence workloads with exascale high-performance computing infrastructure, enabling enterprises to run very large models and data-intensive training or inference on exaflop-class systems within governed, scalable architectures.

• Exascale Application Portability

  Exascale application portability is the capability for software to run correctly and efficiently across different exascale high-performance computing systems without major redesign, enabling organizations to reuse complex simulation, AI, and analytics codes across evolving heterogeneous architectures and deployment environments.

• Exascale Computing

  Exascale computing is the class of high-performance computing systems that sustain at least one exaflop, or 10^18 floating-point operations per second, enabling enterprises and research institutions to run large-scale simulations and data-intensive workloads that exceed conventional data center capabilities.

• Exascale I/O Stack

  Exascale I/O stack is the layered architecture of hardware, software, and protocols that manages input/output for exascale high-performance computing systems, guiding how enterprises design scalable storage and data paths for large simulations, analytics, and AI workloads at extreme scale.

• Exascale Simulation

  Exascale simulation uses exascale high performance computing systems delivering at least 10^18 floating point operations per second to run large, high-fidelity numerical models, enabling enterprises and research institutions to analyze complex systems, support virtual prototyping, and inform quantitative decision-making at large computational scales.