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Data Analytics: Exploiting the Data Warehouse

  • Alejandro Vaisman
  • Esteban Zimányi
Chapter
  • 5k Downloads
Part of the Data-Centric Systems and Applications book series (DCSA)

Abstract

Analytics can be defined as the discovery and communication of meaningful patterns in data. Organizations apply analytics to their data in order to describe, predict, and improve organizational performance. Analytics uses descriptive and predictive models to gain valuable knowledge from data and uses this insight to guide decision making. Analytics relies on data visualization to communicate insight. We can distinguish several variations of analytics depending on the kind of data to be analyzed. While data analytics copes with traditional structured data, text analytics refers to the analysis of unstructured textual sources such as those found in blogs, social networks, and the like. Web analytics refers to the collection, analysis, and reporting of web data. Finally, visual analytics combines automated analysis techniques with interactive visualizations, providing effective means to interactively explore large and complex data sets for decision making.

Keywords

Association Rule Data Warehouse Minimum Support Gini Index Frequent Itemsets 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Alejandro Vaisman
    • 1
  • Esteban Zimányi
    • 2
  1. 1.Instituto Tecnológico de Buenos AiresBuenos AiresArgentina
  2. 2.Université Libre de BruxellesBrusselsBelgium

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