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Edge Computing
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Edge Computing

Definition updated on November 2023

What is edge computing?

Edge computing refers to the computing processes performed at or near the source of data generation, as opposed to relying on centralized cloud-based services. It is designed to minimize latency and reduce bandwidth usage by performing data processing locally.

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Multi-Dimensional Analysis
What is multi-dimensional analysis?
M
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Metadata Harvesting
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M
🏭
Machine Data
What is machine data?
M
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Logical Data Model
What is a logical data model?
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Legacy Data Integration
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Linked Data
What is linked data?
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Lagrangian Data Analysis
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Information Architecture
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Knowledge Graph
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Key Performance Indicators (KPI)
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JSON Data Interchange Format
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In-Memory Computing
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Internet of Things (IoT) Data
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Information Theory
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Feature Extraction
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Indexing and Searching
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Incremental Learning
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I
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Hybrid Data Models
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Homomorphic Encryption
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High-Performance Computing
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Heuristic Analysis
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Hierarchical Data Format
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Differential Privacy
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D
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Graph Databases
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Forensic Data Analysis
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File Format Conversion
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Field-Level Encryption
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Federated Learning
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Extract, Load, Transform (ELT)
What is Extract, Load, Transform (ELT)?
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Enterprise Data Management
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Entity Resolution
What is entity resolution?
E
🗃️
Document Storage
What is document storage?
D
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Dimensional Modeling
What is dimensional modeling?
D
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Diagnostic Analytics
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D
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Digital Forensics
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D
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Descriptive Analytics
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D
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Data Visualization Tools
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D
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Decision Support Systems
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D
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Database Design
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D
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Database Indexing
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D
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Data Value Chain
What is the data value chain?
D
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Data Utilization
What is data utilization?
D
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Data Traffic Analysis
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D
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Data Transformation Services
What are data transformation services?
D
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Data Transmutation
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D
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Data Taxonomy
What is data taxonomy?
D
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Data Tracing
What is data tracing?
D
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Data Subsetting
What is data subsetting?
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Data Structuring
What is data structuring?
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Data Streaming
What is data streaming?
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Data Steward
Who is a data steward?
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Data Serialization
What is data serialization?
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Data Semantics
What are data semantics?
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Data Science Platforms
What are data science platforms?
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Data Retention
What is data retention?
D
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Data Reconciliation
What is data reconciliation?
D
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Data Resilience
What is data resilience?
D
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Data Recovery
What is data recovery?
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Data Readiness Levels
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Data Refinement
What is data refinement?
D
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Data Registries
What are data registries?
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Data Reduction
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D
✔️
Data Quality Assurance
What is data quality assurance?
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Data Orchestration
What is data orchestration?
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Data Operations (DataOps)
What are Data Operations (DataOps)?
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Data Obfuscation
What is data obfuscation?
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Data Literacy
What is data literacy?
D
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Data Discovery
What is data discovery?
D
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Data Curation
What is data curation?
D
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Data Blending
What is data blending?
D
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Data Migration
What is data migration?
D
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Data Normalization
What is data normalization?
D
♻️
Data Deduplication
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D
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Data Profiling
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D
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Data Mashup
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D
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Data Enrichment
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D
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Master Data Management
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M
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Data Staging
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D
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Data Cleansing
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D
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Data Lifecycle Management
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Data Standards
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D
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Quantitative Analysis
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Q
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Metadata Management
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M
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Data Federation
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D
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Knowledge Discovery
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K
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Data Provenance
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D
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Information Retrieval
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I
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Data Marts
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D
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Data Modeling
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D
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Open-Source Software Licensing
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Patent Filings
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P
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Terms of Use and Privacy Policies
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T
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API Terms of Service
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A
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Copyright Infringement Detection
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Trademark Protection
What is trademark protection?
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DMCA Takedown Notices
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Anti-Piracy Measures
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A
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Digital Rights Management
What is digital rights management?
D
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Software Licensing
What is software licensing?
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Legal and Regulatory Frameworks
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