A System for Big Data Analytics over Diverse Data Processing Platforms

Jorge Quiane, Divy Agrawal, Sanjay Chawla, Ahmed Khalifa Elmagarmid, Zoi Kaoudi, Mourad Ouzzani, Paolo Papotti, Nan Tang, Mohammed J. Zaki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data analytics is at the core of any organization that wants to obtain measurable value from its growing data assets. Data analytic tasks may range from simple to extremely complex pipelines, such as data extraction, transformation and loading, online analytical processing, graph processing, and machine learning (ML). Following the dictum “one size does not fit all”, academia and industry have embarked on a race of developing data processing platforms for supporting all of these different tasks, e.g., DBMSs and MapReduce-like systems. Semantic completeness, high performance and scalability are key objectives of such platforms. While there have been major achievements in these objectives, users are still faced with many road-blocks.
Original languageEnglish
Title of host publicationQatar Foundation Annual Research Conference Proceedings
Volume2016
Edition1
DOIs
Publication statusPublished - Mar 2016

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