Data Model Logger - Data Discovery for Extract-Transform-Load

Manik Madhikermi, Andrea Buda, Bhargav Dave, Kary Främling

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

3 Sitaatiot (Scopus)

Abstrakti

Information Systems (ISs) are fundamental to streamline operations and support processes of any modern enterprise. Being able to perform analytics over the data managed in various enterprise ISs is becoming increasingly important for
organisational growth. Extract, Transform, and Load (ETL) are the necessary pre-processing steps of any data mining activity. Due to the complexity of modern IS, extracting data is becoming increasingly complicated and time-consuming. In order to ease the process, this paper proposes a methodology and a pilot implementation, that aims to simplify data extraction process by leveraging the end-users’ knowledge and understanding of the specific IS. This paper first provides a brief introduction and the current state of the art regarding existing ETL process and techniques. Then, it explains in details the proposed methodology. Finally, test results of typical data-extraction tasks from 4 commercial ISs are reported.
AlkuperäiskieliEnglanti
Otsikko2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
KustantajaIEEE
Sivut629-630
ISBN (painettu)978-1-5386-2588-0
DOI - pysyväislinkit
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE International Conference on Data Science and Systems - Bangkok, Thaimaa
Kesto: 18 joulukuuta 201720 joulukuuta 2017
Konferenssinumero: 3

Conference

ConferenceIEEE International Conference on Data Science and Systems
LyhennettäDSS
Maa/AlueThaimaa
KaupunkiBangkok
Ajanjakso18/12/201720/12/2017

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