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Setting Up a Big Data Project: Challenges, Opportunities, Technologies and Optimization

Roberto V. Zicari, Marten Rosselli, Todor Ivanov, Nikolaos Korfiatis, Karsten Tolle, Raik Niemann, Christoph Reichenbach

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Abstract

In the first part of this chapter we illustrate how a big data project can be set up and optimized. We explain the general value of big data analytics for the enterprise and how value can be derived by analyzing big data. We go on to introduce the characteristics of big data projects and how such projects can be set up, optimized and managed. Two exemplary real word use cases of big data projects are described at the end of the first part. To be able to choose the optimal big data tools for given requirements, the relevant technologies for handling big data are outlined in the second part of this chapter. This part includes technologies such as NoSQL and NewSQL systems, in-memory databases, analytical platforms and Hadoop based solutions. Finally, the chapter is concluded with an overview over big data

Original languageEnglish
Title of host publicationBig Data Optimization
Subtitle of host publicationRecent Developments and Challenges
Editors/authorsAli Emrouznejad
PublisherSpringer
Pages17-47
Number of pages31
Volume18
ISBN (Electronic)978-3-319-30265-2
ISBN (Print)978-3-319-30263-8
DOIs
Publication statusPublished - 2016
Externally publishedYes

Publication series

NameStudies in Big Data
PublisherSpringer
Volume18
ISSN (Print)2197-6503
ISSN (Electronic)2197-6511

Subject classification (UKÄ)

  • Other Computer and Information Science

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