With the recent developments of Internet of Things (IoT) and cloudbased technologies, massive amounts of data are generated by heterogeneous sources and stored through dedicated cloud solutions. Often organizations generate much more data than they are able to interpret, and current Cloud Computing technologies cannot fully meet the requirements of the Big Data processing applications and their data transfer overheads. Many data are stored for compliance purposes only but not turned into value, thus becoming Dark Data, which are not only an unused value but also pose a risk for organizations.
Towards a Framework for Data Pipeline Discovery / Benvenuti, Dario. - (2023), pp. 293-294. (Intervento presentato al convegno Sigmod 2023 tenutosi a Seattle) [10.1145/3555041.3589395].
Towards a Framework for Data Pipeline Discovery
Dario Benvenuti
2023
Abstract
With the recent developments of Internet of Things (IoT) and cloudbased technologies, massive amounts of data are generated by heterogeneous sources and stored through dedicated cloud solutions. Often organizations generate much more data than they are able to interpret, and current Cloud Computing technologies cannot fully meet the requirements of the Big Data processing applications and their data transfer overheads. Many data are stored for compliance purposes only but not turned into value, thus becoming Dark Data, which are not only an unused value but also pose a risk for organizations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.