DataTerminology.comNEW
Reinterpretable representation of information in a formalized manner suitable for communication and processing.
DESCRIPTION
Data are representations of facts, observations, or measurements encoded for storage, transmission, and computation. They may be structured, semi-structured, or unstructured, and require context (metadata) to become meaningful information. Managing data across its lifecycle—creation, acquisition, transformation, use, sharing, retention, and disposal—is central to enterprise value and compliance. Clarity on definitions, standards, and ownership underpins data quality and governance.
ALTERNATIVE DEFINITIONS
ISO/IEC 2382:2015
data: reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing.
Formal, standardized definition from international vocabulary.
Wikipedia
Data are individual facts, statistics, or items of information, often numeric.
Plain-language characterization emphasizing facts and statistics.
RELATED TERMS
Knowledge Metadata Dataset Data Quality Governance Data Lifecycle Data Model Provenance Data Stewardship
COMPETING TERMS
RELATIONS
- Narrower: Amalgamated Data Ancillary Data Big Data Biological Data Calibration Data Categorical Data Clinical Data Continuous Data Count Data Domain-Oriented Data Enterprise Structure Data European Strategy for Data FAIR Data Geographic Data Geographic-Geo-Statistical Data Health Data Heterogeneous Data Hierarchical Data High Frequency Data Homogeneous Data Imbalanced Data Instance Data Labeled Data Late Data Linked Data Market Data Master Data Missing Data Model Data Monte Carlo Data Non-Personal Data Open Data Open Government Data Ordinal Data Panel Data Parametric Data Poisson Data Project Management Data Qualitative Data Quantitative Data Raw Data Real-time Data Reference Data Semi-structured Data Sensitive Data Streaming Data Structured Data Tabular Data Temporal Data Third-Party Data Time-Series Data Training Data Transaction Activity Data Transaction Audit Data Transaction Structure Data Transactional Data Unlabeled Data Validation Data
KNOWLEDGE AREAS
Data Management Metadata Management Data Architecture Domain & Business Context
TARGET AUDIENCE
Chief Data Officer Data Governance Manager Data Steward Data Architect Enterprise Architect Data Strategy Consultant Information Analyst
EXTERNAL SOURCES
TOP QUESTIONS
How does Data differ from Information?
Data are raw, encoded representations; information is data interpreted within context to convey meaning. Metadata often provides the needed context to transform data into information.
Category: Concept
Why is Data governance important?
Governance ensures data is accurate, secure, and usable, enabling trust and compliance. It assigns roles, policies, and controls across the data lifecycle.
Category: Relevancy
What types of Data exist?
Structured (tables), semi-structured (JSON), and unstructured (text, media). Each requires different storage, processing, and governance approaches.
Category: Overview
What is the Data lifecycle?
Creation, acquisition, storage, transformation, use, sharing, retention, and disposal. Each stage demands controls, quality checks, and documentation.
Category: Explanation
Who owns Data in an organization?
Data ownership is assigned to business domains or roles through governance. Data stewards and owners are accountable for quality and access policies.
Category: Governance
Why is Metadata essential for Data?
Metadata provides meaning, lineage, and usage rules, enabling discovery, quality assessment, and compliance. Without metadata, data is hard to interpret and trust.
Category: Requirements
How is Data quality measured?
Common dimensions include accuracy, completeness, timeliness, consistency, and uniqueness. Metrics and rules track and improve fitness for purpose.
Category: Quality
What risks arise from poor Data management?
Decisions degrade, regulatory penalties increase, and costs escalate. Data breaches and inappropriate use further harm reputation and trust.
Category: Risks
How do standards help define Data consistently?
Standards like ISO/IEC 2382 and ISO 8000 create shared definitions and quality principles. They foster interoperability and uniform governance.
Category: Standards