TY - GEN
T1 - Big data etl implementation approaches
T2 - 30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018
AU - Nwokeji, Joshua C.
AU - Aqlan, Faisal
AU - Apoorva, Anugu
AU - Olagunju, Ayodele
N1 - Publisher Copyright:
© 2018 Universitat zu Koln. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Extract, transform, load (ETL) is an essential technique for integrating data from multiple sources into a data warehouse. ETL is applicable to data warehousing, big data, and business intelligence. Through a systematic literature review of 97 papers, this research identifies and evaluates the current approaches used to implement existing ETL solutions. We found that conceptual modeling such as UML, BPMN, and MDA is the most popular approach used to implement ETL solutions. However, innovative approaches such as machine learning, artificial intelligence, and robotics are either under-utilized or not used at all to develop ETL solutions. Additionally, we discuss the implications of these to ETL research and practice.
AB - Extract, transform, load (ETL) is an essential technique for integrating data from multiple sources into a data warehouse. ETL is applicable to data warehousing, big data, and business intelligence. Through a systematic literature review of 97 papers, this research identifies and evaluates the current approaches used to implement existing ETL solutions. We found that conceptual modeling such as UML, BPMN, and MDA is the most popular approach used to implement ETL solutions. However, innovative approaches such as machine learning, artificial intelligence, and robotics are either under-utilized or not used at all to develop ETL solutions. Additionally, we discuss the implications of these to ETL research and practice.
UR - http://www.scopus.com/inward/record.url?scp=85056896373&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056896373&partnerID=8YFLogxK
U2 - 10.18293/SEKE2018-152
DO - 10.18293/SEKE2018-152
M3 - Conference contribution
AN - SCOPUS:85056896373
T3 - Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
SP - 714
EP - 715
BT - Proceedings - SEKE 2018
PB - Knowledge Systems Institute Graduate School
Y2 - 1 July 2018 through 3 July 2018
ER -