Data is a representation of facts, concepts, or instructions in a formalized manner, suitable for communication, interpretation, or processing by humans or by automatic means.

Data represents facts/things other than itself. Data is both an interpretation of the objects it represents and an object that must be interpreted.

Data is a business asset, while not tangible, it has value and can be managed.

See data quality dimensions.

The life cycle of data in alphabetical order is:

• Add data
• Aggregate data
• Align data
• Analyse data
• Annotate data
• Anonymize data
• Archive data
• Arrange data
• Apply data
• Assess data
• Audit data
• Benchmark data
• Blend data
• Calculate data
• Capture data
• Categorize data
• Change data
• Classify data
• Clean or cleans data (data cleansings)
• Cluster data
• Collect data
• Compare data
• Complete data
• Compress data
• Consolidate data
• Consume data
• Convert data
• Copy data
• Correlate data
• Correct data
• Create data
• Cross-reference data
• Decode data
• Decrypt data
• De-duplicate data
• De-identify data
• Delete data
• Deliver data
• Describe data
• Design data (data design)
• Detect data
• Differentiate data
• Disaggregate data
• Disponse data
• Distribute data
• Dispose data
• Encode data
• Encrypt data
• Enrich data
• Evaluate data
• Expand data
• Export data
• Extract data
• Extrapolate data
• Filter data
• Forecast data
• Generate data
• Group data
• Harmonize data
• Highlight data
• Identify data
• Import data
• Impute data
• Index data
• Infer data
• Insert data
• Integrate data (data integration}
• Interpolate date
• Interpret data
• Isolate data
• Link data
• Locate data
• Maintain data
• Map data
• Merge data
• Migrate data
• Mine data
• Model data (data modeling | data model)
• Monetize data
• Move data
• Normalize data
• Observe data
• Optimize data
• Organize data
• Partition data
• Present data
• Process data
• Procure data
• Protect data
• Pseudonymize data
• Publish data
• Reconcile data
• Record data
• Reformat data
• Regulate data
• Report data
• Retain data
• Reuse data
• Review data
• Secure data (data security)
• Segment data
• Share data
• Standardize data
• Store data (data storage | data store)
• Stucture data (data structuring | data structure)
• Summarize data
• Use data
• Validate data
• Verify data
• Visualize data

DAMA NL (2020). Data concepts for Data Quality Dimensions (DSC). Research paper. https://www.dama-nl.org/wp-content/uploads/2020/09/DCS-Data-Concept-System-DDQ-Research-Paper-version-1.2-d.d.-3-Sept-2020.pdf

ISO 2382-4.Information technology — Vocabulary — Part 4: Organization of data.