Visualization Tools for Big Data analytics in Quantitative Chemical Analysis

Dumancas, G, Bello, G, Hughes, J, Murimi, R, Viswanath, L, Orndoff, C, Fe Dumancas, G and O'Dell, J 2018, 'Visualization Tools for Big Data analytics in Quantitative Chemical Analysis' in Richard S. Segall and Jeffrey S. Cook (ed.) Handbook of research on big data storage and visualization techniques, IGI Global, Hershey, Pennsylvania, USA, pp. 873-917.


Document type: Book Chapter
Collection: Book Chapters

Title Visualization Tools for Big Data analytics in Quantitative Chemical Analysis
Author(s) Dumancas, G
Bello, G
Hughes, J
Murimi, R
Viswanath, L
Orndoff, C
Fe Dumancas, G
O'Dell, J
Year 2018
Title of book Handbook of research on big data storage and visualization techniques
Publisher IGI Global
Place of publication Hershey, Pennsylvania, USA
Editor(s) Richard S. Segall and Jeffrey S. Cook
Start page 873
End page 917
Subjects Analytical Chemistry not elsewhere classified
Pattern Recognition and Data Mining
Summary 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.
Copyright notice © 2018, IGI Global.
Keyword(s) Analytics
Architecture Patterns
Clouds and Clusters
Computational Business Intelligence
Computational Energy Programming Systems
Technologies
ISBN 9781522531425
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