DocumentCode :
1791638
Title :
Automating data integration with HiperFuse
Author :
Huang, Edward ; Quiroz, Andres ; Ceriani, Luca
Author_Institution :
Palo Alto Res. Center, Interaction & Analytics Lab., Palo Alto, CA, USA
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
863
Lastpage :
867
Abstract :
Integrating heterogeneous datasets has been a significant barrier to many analytics tasks, due to the variety in structure and level of cleanliness of raw datasets requiring one-off ETL code. We propose HiperFuse, which significantly automates the data integration process by providing a declarative interface, robust type inference, extensible domain-specific data models, and a data integration planner which optimizes for plan completion time.
Keywords :
data integration; data models; HiperFuse; data integration planner; declarative interface; extensible domain-specific data models; heterogeneous dataset integration; one-off ETL code; robust type inference; Benchmark testing; Computational modeling; Data integration; Data models; IP networks; Libraries; Planning; DSL; ETL; automation; data fusion; data integration; dataflow optimization; declarative; planning; scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/BigData.2014.7004316
Filename :
7004316
Link To Document :
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