Visualization tools for big data analytics in quantitative chemical analysis: A tutorial in chemometrics

Gerard G. Dumancas, Ghalib A. Bello, Jeff Hughes, Renita Murimi, Lakshmi Chockalingam Kasi Viswanath, Casey O.Neal Orndorff, Glenda Fe Dumancas, Jacy D. O'Dell

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

Modern instruments have the capacity to generate and store enormous volumes of data and the challenges involved in processing, analyzing and visualizing this data are well recognized. The field of Chemometrics (a subspecialty of Analytical Chemistry) grew out of efforts to develop a toolbox of statistical and computer applications for data processing and analysis. This chapter will discuss key concepts of Big Data Analytics within the context of Analytical Chemistry. The chapter will devote particular emphasis on preprocessing techniques, statistical and Machine Learning methodology for data mining and analysis, tools for big data visualization and state-of-the-art applications for data storage. Various statistical techniques used for the analysis of Big Data in Chemometrics are introduced. This chapter also gives an overview of computational tools for Big Data Analytics for Analytical Chemistry. The chapter concludes with the discussion of latest platforms and programming tools for Big Data storage like Hadoop, Apache Hive, Spark, Google Bigtable, and more.

Original languageEnglish
Title of host publicationHandbook of Research on Big Data Storage and Visualization Techniques
PublisherIGI Global
Pages873-917
Number of pages45
ISBN (Electronic)9781522531432
ISBN (Print)1522529934, 9781522529934
DOIs
StatePublished - 5 Jan 2018
Externally publishedYes

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