Description

Current tools that facilitate the extract-transform-load (ETL) process focus on ETL workflow, not on generating meaningful semantic relationships to integrate data from multiple, heterogeneous sources. A proposed semantic ETL framework

Current tools that facilitate the extract-transform-load (ETL) process focus on ETL workflow, not on generating meaningful semantic relationships to integrate data from multiple, heterogeneous sources. A proposed semantic ETL framework applies semantics to various data fields and so allows richer data integration.

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Date Created
  • 2015-03-01
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  • Text
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    Identifier
    • Digital object identifier: 10.1109/MC.2015.76
    • Identifier Type
      International standard serial number
      Identifier Value
      0018-9162
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    • Copyright 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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    Bansal, Srividya K., & Kagemann, Sebastian (2015). Integrating Big Data: A Semantic Extract-Transform-Load Framework. COMPUTER, 48(3), 42-50. http://dx.doi.org/10.1109/MC.2015.76

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