In the era of Big Data and AI, it is challenging to know all technical and business advantages of the emerging technologies. The goal of DataBench is to design a benchmarking process helping organizations developing Big Data Technologies (BDT) to reach for excellence and constantly improve their performance, by measuring their technology development activity against parameters of high business relevance. This paper focuses on the internals of the DataBench framework and presents our methodological workflow and framework architecture.

Building the databench workflow and architecture

Pernici B.;Francalanci C.
2020-01-01

Abstract

In the era of Big Data and AI, it is challenging to know all technical and business advantages of the emerging technologies. The goal of DataBench is to design a benchmarking process helping organizations developing Big Data Technologies (BDT) to reach for excellence and constantly improve their performance, by measuring their technology development activity against parameters of high business relevance. This paper focuses on the internals of the DataBench framework and presents our methodological workflow and framework architecture.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
978-3-030-49555-8
978-3-030-49556-5
Benchmarking
Big Data
DataBench
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1146756
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