Can I read Distributed Data Analytics on EtoBox?

Distributed Data Analytics by Mortier, Richard; Haddadi, Hamed; Servia, Sandra; Wang, Liang is a scholarly article available to read on EtoBox.

What is Distributed Data Analytics about?

Machine Learning (ML) techniques have begun to dominate data analytics applications and services. Recommendation systems are a key component of online service providers. The financial industry has adopted ML to harness large volumes of data in areas such as fraud detection, risk-management, and compliance. Deep Learning is the technology behind voice-based personal assistants, etc. Deployment of ML technologies onto cloud computing infrastructures has benefited numerous aspects of our daily life. The advertising and associated online industries in particular have fuelled a rapid rise the in deployment of personal data collection and analytics tools. Traditionally, behavioural analytics relies on collecting vast amounts of data in centralised cloud infrastructure before using it to train machine learning models that allow user behaviour and preferences to be inferred. A contrasting approach, distributed data analytics, where code and models for training and inference are distributed to the places where data is collected, has been boosted by two recent, ongoing developments: increased processing power and memory capacity available in user devices at the edge of the network, such as s

Author

Mortier, Richard; Haddadi, Hamed; Servia, Sandra; Wang, Liang

Published

2022

Language

EN