Can Data Integration Quality be Enhanced on Multi-cloud using SLA?

International audienceThis paper identifies trends and open issues regarding the useof SLA in data integration solutions on multi-cloud environments. Therefore it presents results of a Systematic Mapping [3] that analyzes the way SLA, data integration and multi-cloud environments are correlated in existing works. The main result is a classification scheme consisting of facets and dimensions namely (i) data integration environment (cloud; data warehouse; federated database; multi-cloud); (ii) data integration description (knowledge; metadata; schema); and (iii) data quality (confidentiality; privacy; security; SLA; data protection; data provenance). The proposed classification scheme is used to organize a collection of representative papers and discuss the numerical analysis about research trends in the domain

Can Data Integration Quality be Enhanced on Multi-cloud using SLA?

International audienceThis paper identifies trends and open issues regarding the useof SLA in data integration solutions on multi-cloud environments. Therefore it presents results of a Systematic Mapping [3] that analyzes the way SLA, data integration and multi-cloud environments are correlated in existing works. The main result is a classification scheme consisting of facets and dimensions namely (i) data integration environment (cloud; data warehouse; federated database; multi-cloud); (ii) data integration description (knowledge; metadata; schema); and (iii) data quality (confidentiality; privacy; security; SLA; data protection; data provenance). The proposed classification scheme is used to organize a collection of representative papers and discuss the numerical analysis about research trends in the domain