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 applies semantics to various data fields and so allows richer data integration.
Copyright Statement
Details
Title
- Integrating Big Data: A Semantic Extract-Transform-Load Framework
Contributors
- Bansal, Srividya (Author)
- Kagemann, Sebastian (Author)
- Ira A. Fulton Schools of Engineering (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2015-03-01
Resource Type
Collections this item is in
Identifier
- Digital object identifier: 10.1109/MC.2015.76
- Identifier TypeInternational standard serial numberIdentifier Value0018-9162
Note
- 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.
Citation and reuse
Cite this item
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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