Data Science technologies

Carlos Carrasco-Farré, Manu Carricano, Didier Grimaldi

Research output: Book chapterChapterpeer-review

Abstract

Data is everywhere. Even when we do not know or think about it, data is being generated because we are surrounded by technology. Therefore, we have the opportunity to leverage on data science to make better and more informed decisions in cities. However, in this chapter, we have not provided an exact definition for data science. In contrast, we do believe that since data science is a relatively new field, it is easier to understand by defining the type of problems that data science deals with; from classification problems to clustering, similarity or causality. In addition, the chapter covers how to organize and manage data science teams and data-intensive projects.

Original languageEnglish
Title of host publicationImplementing Data-Driven Strategies in Smart Cities
Subtitle of host publicationA Roadmap for Urban Transformation
PublisherElsevier
Pages89-110
Number of pages22
ISBN (Electronic)9780128211229
ISBN (Print)9780128211236
DOIs
Publication statusPublished - 1 Jan 2021

Keywords

  • Big Data
  • Data science
  • Data-driven project
  • Handle urban issues
  • Predictive
  • Prescriptive

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