Enterprise Technology Glossary

6,173 results · page 69 of 309

• Data Dependency Graph

  Data dependency graph is a directed graph representation that models how data elements and computations depend on each other in software, analytics, or data workflows, enabling structured analysis, optimization, impact assessment, and governance in enterprise-scale systems and data platforms.

• Data Diode

  Data diode is a hardware-enforced unidirectional network device that permits data to flow only in one direction between networks, used to export information from high-security or safety-critical environments while reducing exposure to inbound cyber threats and remote compromise.

• Data Discovery

  Data discovery is the process and tooling that scan, profile, classify, and catalog enterprise data assets so organizations know what data they have, where it resides, and how it is used, supporting governance, security, compliance, and analytics use cases.

• Data Downlink

  Data downlink is the transfer of data from a remote platform, such as a satellite, spacecraft, aircraft, or unmanned system, to ground-based receivers, supporting telemetry, payload delivery, and enterprise data ingestion for monitoring, analytics, and operational decision processes.

• Data Downlink Station

  Data downlink station is a ground-based facility that receives, demodulates, and processes data transmitted from satellites or aerial platforms into digital streams for terrestrial networks, affecting availability, latency, and security of space-derived data used in enterprise operations and services.

• Data Drift

  Data drift is the change over time in the statistical properties of input data used by a model or analytics system compared with its training or baseline data, and it matters because unmanaged drift can degrade reliability and require governance action.

• Data Drift Analysis

  Data drift analysis is the process of monitoring and quantifying changes in production data distributions relative to a baseline, used by enterprises to maintain machine learning model reliability, support retraining decisions, and document oversight within MLOps and model governance workflows.

• Data Drift Detection

  Data drift detection is the process of monitoring changes in the statistical properties of data over time to identify when deployed analytical or machine learning models operate under conditions different from their training data, supporting governance, reliability, and model risk management.

• Data Drift Monitor

  Data Drift Monitor is a monitoring capability that quantifies changes in the statistical properties of production data compared with reference data, enabling enterprises to detect data shifts that may affect model performance, compliance controls, and data quality governance processes.

• Data-Driven Alert Suppression

  Data-driven alert suppression is a method in security and observability systems that uses analytical models, rules, and historical data to automatically mute or reduce redundant and low-value alerts, helping enterprises control alert volume while maintaining policy and monitoring requirements.

• Data-Driven Decision Platform

  Data-driven decision platform is an integrated software environment that collects, manages, and analyzes data to support repeatable, auditable decisions in enterprises, providing shared infrastructure for analytics, decision services, and governance across business and technology functions.

• Data-Driven Test Prioritization

  Data-driven test prioritization is a software testing method that orders test cases using quantitative evidence from code, tests, and runtime data so higher-risk or higher-value checks run earlier, supporting risk-based regression testing and constrained release timelines in enterprise environments.

• Data Durability

  Data durability is the quantified probability that stored data remains intact and retrievable over time without loss. It matters in enterprise contexts because it underpins compliance, continuity, and risk decisions for storage platforms, backups, archives, and disaster recovery architectures.

• Data Egress Optimization

  Data egress optimization is the practice of controlling and reducing outbound data transfers from clouds, data centers, and networks to manage cost, bandwidth, and compliance while maintaining required performance, security, and availability for enterprise workloads and data flows.

• Data Encoding Layer

  Data encoding layer is an architectural component that converts raw data into standardized encoded representations for storage, transmission, and processing, enabling consistent interoperability, performance tuning, and controlled data handling across enterprise applications, integration platforms, and communication or storage systems.

• Data Encryption

  Data encryption is a cryptographic process that converts readable data into ciphertext using algorithms and keys, enabling enterprises to protect confidentiality of data at rest and in transit, meet regulatory requirements, and reduce exposure from unauthorized access or interception.

• Data Encryption At Rest

  Data encryption at rest is the application of cryptography to data stored on persistent media so it remains unreadable without decryption keys, helping enterprises address storage-related threats, regulatory requirements, and internal security policies for databases, files, backups, and cloud storage.

• Data Encryption In Transit

  Data encryption in transit protects data confidentiality and integrity while it moves between endpoints, networks, or cloud services using cryptographic protocols and keys. It matters in enterprises because regulations, zero trust architectures, and security baselines require protected communications across internal and external connections.

• Data Encryption Key

  Data encryption key is a cryptographic key used to encrypt and decrypt data in enterprise systems, typically within a hierarchical key management architecture, and is central to enforcing confidentiality controls and meeting security and compliance requirements for data at rest and in transit.

• Data Encryption Standard

  Data Encryption Standard (DES) is a symmetric-key block cipher that encrypts 64-bit data blocks with a 56-bit key and served as a U.S. federal standard; in enterprises it now appears mainly in legacy systems and deprecation planning.