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P-ETL: Parallel-ETL based on the MapReduce paradigm

2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), 2014
Big data is an opportunity in the emergence of novel business applications such as “Big Data Analytics” (BDA). However, these data with non-traditional volumes create a real problem given the capacity constraints of traditional systems. The aim of this paper is to deal with the impact of big data in a decision-support environment and more particularly ...
Mahfoud Bala   +2 more
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E-ETL

Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management, 2011
External data sources (EDSs) being integrated in a data warehouse (DW) frequently change their data structures (schemas). As a consequence, in many cases, an already deployed ETL workflow executes with errors. Since structural changes of EDSs are frequent, an automatic reparation of an ETL workflow after such changes is of a high importance.
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A semantic approach to ETL technologies

Data & Knowledge Engineering, 2011
Data warehouse architectures rely on extraction, transformation and loading (ETL) processes for the creation of an updated, consistent and materialized view of a set of data sources. In this paper, we support these processes by proposing a tool that: (1) allows the semi-automatic definition of inter-attribute semantic mappings, by identifying the parts
Sonia Bergamaschi   +4 more
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Principles for an ETL Benchmark

2009
Conditions in the marketplace for ETL tools suggest that an industry standard benchmark is needed. The benchmark should provide useful data for comparing the performance of ETL systems, be based on a meaningful scenario, and be scalable over a wide range of data set sizes.
Len Wyatt, Brian Caufield, Daniel Pol
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Trajectory ETL Modeling

2017
Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from heterogeneous sources, their cleansing, customization and insertion into data warehouse. In fact, ETL are the key component of data warehousing process because incorrect or misleading data will produce wrong business decisions.
Assawer Zekri   +3 more
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