Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : INRAe
Durée : 6
Contact : sandro.bimonte@irstea.fr
Date limite de publication : 2020-01-15
Contexte :
**!!!!!The internship grant scientific work is based on our new paper that will appear at DOLAP2020 : “To Each His Own: Accommodating Data Variety by a Multimodel Star Schema”. !!!!!
Sujet :
**Our proposal is a preliminary work that define DW schema inside Multimodel databases [1]. In particular, on using a multimodel (MM) star schema to deal with variety in data warehouses (DW) where the same schema may contain different data types that are not necessarily structured.
The paper is a “preliminary investigation” and thus there are not many conclusive findings, but the paper introduces the basics and points to many directions for future work. The topic is very important in this era of big data management and for many real-life applications.
Some directions of this future work will investigated during the internship.
**In particular, we will provide some methods and tests to “measure” the benefit of our approach against relational and single NoSQL model for: (i) variety, (ii) flexibility, and (iii) ETL
A real case study concerning agricultural tractors and robots data (i.e. trajectory data) will be used during the project.
[1] Jiaheng Lu and Irena Holubová. 2019. Multi-model
Databases: A New Journey to Handle the Variety of Data.ACM
Comput. Surv.52, 3 (2019), 55:1–55:38
Profil du candidat :
**Required skills:
Data Warehouse
Databases
ETL
Spatial data (optional)
Mondrian OLAP server (optional)
Formation et compétences requises :
Data Warehouse
Databases
ETL
Spatial data (optional)
Mondrian OLAP server (optional)
Adresse d’emploi :
INRAe 9 avenue Blaise Pascal
Aubiere France