Data Visualization and Analytics

Author:   Mauricio Alberto Ortega Ruiz
Publisher:   Toronto Academic Press
ISBN:  

9781779568830


Publication Date:   15 January 2026
Format:   Paperback
Availability:   In Print   Availability explained
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Data Visualization and Analytics


Overview

In the era of big data, visualizing information effectively enables organizations to make informed decisions and communicate insights clearly. Data visualization transforms complex datasets into accessible, meaningful narratives. Data Visualization and Analytics explores the principles, tools, and techniques for analyzing and presenting data. The book discusses visual design best practices, statistical interpretation, and storytelling with data. It also introduces visualization software such as Tableau, Power BI, and Python-based libraries. Combining theory with practical applications, it equips analysts, researchers, and decision-makers with the skills to convert data into actionable knowledge.

Full Product Details

Author:   Mauricio Alberto Ortega Ruiz
Publisher:   Toronto Academic Press
Imprint:   Toronto Academic Press
ISBN:  

9781779568830


ISBN 10:   1779568835
Publication Date:   15 January 2026
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Author Information

Mauricio Alberto Ortega-Ruíz is an Electrical Engineering graduated from UNAM at Mexico, with experience in technical support for electronics equipment, field service and training services. This experience accomplishes instrumentation equipment, photo-lab and automation industry. Mauricio's academic journey includes a M. Sc. in signal processing at the Imperial College of Science Technology and Medicine and a PhD at City University of London, both are UK Universities. His main Research interest is in AI applications for medical imaging analysis and particularly in digital histopathology for breast cancer grading, he has published Scientific papers on this topic and participated in the Automated Gleason Grand Challenge 2022 in which he developed Deep Learning methods for Prostate cancer image grading and obtained the 10th place in the final ranking. He is cofounder of DigPatho, a research group for the LATAM region. Besides his passion for Research in the medical image field he has also demonstrated interest in signal processing, and other imaging applications. He dedicates time to culture and music, and as an amateur violist, he was member of the Imperial College Chamber orchestra during his masters.

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