Data Source

A Data Source is a system component that provides data sets (to support data-driven processes and data-driven systems).

• Context:
  • It can generate Data Content through data generation mechanisms.
  • It can provide Data Access via access interfaces.
  • It can maintain Data Format through format specifications.
  • It can ensure Data Quality via quality controls.
  • It can support Data Availability through delivery mechanisms.
  • It can often include Data Schema with structural elements.
  • It can often enable Data Discovery through metadata services.
  • It can often support Data Integration via integration protocols.
  • It can often maintain Data Freshness through update mechanisms.
  • ...
  • It can range from being a Batch Data Source to being a Real-Time Data Source, depending on its delivery mode.
  • It can range from being a Static Data Source to being a Dynamic Data Source, depending on its update frequency.
  • It can range from being a Simple Data Source to being a Complex Data Source, depending on its data structure.
  • It can range from being a Raw Data Source to being a Processed Data Source, depending on its processing level.
  • It can range from being a Single Data Source to being a Federated Data Source, depending on its distribution model.
  • It can range from being a Structured Data Source to being an Unstructured Data Source, depending on its data format.
  • It can range from being a Point Data Source to being a Data Flow Source, depending on its temporal continuity.
  • ...
  • It can integrate with Data Consumer for data consumption.
  • It can connect to Data Pipeline for data flow.
  • It can support Data Repository for data storage.
  • ...
• Example(s):
  • Enterprise Data Sources, such as:
    • Market Data Systems, such as:
      • New York Stock Exchange Data Feed for financial trading.
      • Bloomberg Data Feed for market analysis.
    • Business Intelligence Sources, such as:
      • Sales Analytics Feed for performance tracking.
      • Customer Data Platform for behavior analysis.
  • Research Data Sources, such as:
    • Academic Repositorys, such as:
      • UCI ML Repository for machine learning.
      • Real-World Dataset for empirical research.
    • Clinical Sources, such as:
      • Clinical Trial Data for medical research.
      • Healthcare Dataset for patient analysis.
  • Technology Data Sources, such as:
    • Stream Systems, such as:
      • Real-Time Data Stream for live monitoring.
      • Event Data Feed for system tracking.
    • Sensor Networks, such as:
      • IoT Sensor Feed for device monitoring.
      • Environmental Sensor for condition tracking.
  • Web Data Sources, such as:
    • Content Feeds, such as:
      • Web Feed for content syndication.
      • RSS Feed for information distribution.
    • E-Commerce Feeds, such as:
      • Product Data Feed for e-commerce.
      • Product Offer Data Feed for retail distribution.
  • AI Training Sources, such as:
    • Model Training Datas, such as:
      • LLM Training Dataset for model training.
      • Multimodal Dataset for AI development.
    • Specialized Corpuses, such as:
      • DEFT Corpus for text analysis.
      • Wikipedia Data Feed for information extraction.
  • Integration Sources, such as:
    • Enterprise Integrations, such as:
      • Integration Server System for data aggregation.
      • AWS Data Pipeline for data orchestration.
    • Data Lake Sources, such as:
      • Data Lake Feed for unified storage.
      • Data Warehouse Stream for analytical processing.
  • Government Data Sources, such as:
    • Public Datasets, such as:
      • Census Data Feed for demographic analysis.
      • Open Government Data for public research.
    • Regulatory Feeds, such as:
      • Compliance Data Stream for regulatory reporting.
      • Policy Update Feed for governance tracking.
  • Social Data Sources, such as:
    • Social Media Feeds, such as:
      • Social Network Stream for engagement analysis.
      • User Generated Content Feed for trend analysis.
    • Community Datas, such as:
      • Forum Data Stream for discussion analysis.
      • Review Platform Feed for sentiment tracking.
  • Weather Data Sources, such as:
    • Meteorological Feeds, such as:
      • Weather Station Data for condition monitoring.
      • Satellite Data Feed for atmospheric analysis.
    • Climate Datas, such as:
      • Historical Climate Feed for trend analysis.
      • Forecast Data Stream for prediction modeling.
  • ...
• Counter-Example(s):
  • Computation Resource, which processes rather than provides data.
  • Data Sink, which consumes rather than provides data.
  • Data Cache, which temporarily stores rather than originates data.
  • Data Proxy, which forwards rather than generates data.
• See: Data Provider, Data Origin, Data System, Data Collection Task, Real-Time Computing, E-Commerce, Internet Marketing.

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References

2024

• (Wikipedia, 2024) ⇒ https://en.wikipedia.org/wiki/Data_feed Retrieved:2024-12-23.
  • Data feed is a mechanism for users to receive updated data from data sources. It is commonly used by real-time applications in point-to-point settings as well as on the World Wide Web. The latter is also called web feed. News feed is a popular form of web feed. RSS feed makes dissemination of blogs easy. Product feeds play increasingly important role in e-commerce and internet marketing, as well as news distribution, financial markets, and cybersecurity. Data feeds usually require structured data that include different labelled fields, such as "title" or "product".

2014

• (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/data_feed Retrieved:2014-2-10.
  • Data feed is a mechanism for users to receive updated data from data sources. It is commonly used by real-time applications in point-to-point settings as well as on the World Wide Web. The latter is also called web feed. News feed is a popular form of web feed. RSS feed makes dissemination of blogs easy. Product feeds play increasingly important role in e-commerce and internet marketing. Data feeds usually requires structured data. At the present time unstructured data, e.g. HTML pages, dominate the Web. As a result, data feeds have the potential to make a bigger impact on the Web in the future.

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