TY - JOUR
T1 - Big Data architecture for water resources management
T2 - A Systematic Mapping Study
AU - Cravero, Ania
AU - Saldana, Orlando
AU - Espinosa, Roberto
AU - Antileo, Christian
N1 - Publisher Copyright:
© 2003-2012 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - The combination of growth in demand for water, climate and hydrological gap, pushed the decision makers and water resource managers to find strategies for effective management of water resources. In this sense, looking for a new technology that allows data processing on a large scale, and with a complex structure, is that it has been using the new generation of Business Intelligence technology, known as Big Data. In recent years, solutions have been proposed for Big Data management issues of water resources in general.
AB - The combination of growth in demand for water, climate and hydrological gap, pushed the decision makers and water resource managers to find strategies for effective management of water resources. In this sense, looking for a new technology that allows data processing on a large scale, and with a complex structure, is that it has been using the new generation of Business Intelligence technology, known as Big Data. In recent years, solutions have been proposed for Big Data management issues of water resources in general.
KW - Big Data
KW - architecture
KW - resources
KW - systematic mapping
KW - water
UR - https://www.scopus.com/pages/publications/85047141040
U2 - 10.1109/TLA.2018.8358672
DO - 10.1109/TLA.2018.8358672
M3 - Article
AN - SCOPUS:85047141040
SN - 1548-0992
VL - 16
SP - 902
EP - 918
JO - IEEE Latin America Transactions
JF - IEEE Latin America Transactions
IS - 3
ER -