Visual Data Storytelling with Tableau - Ryan, Lindy
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Présentation Visual Data Storytelling With Tableau Format Broché
- Livre Informatique
Résumé : The modules in this book will go beyond the dashboard to communicate business-relevant implications of data analyses using the analytic, visualization, and storytelling capabilities of Tableau, the most popular visualization software in use by businesses world today. Each chapter will split focus between discussing key components of design practice and data visualization and introducing a format for representing information with step-by-step guides for using Tableau. By the end of this book, readers will not only understand how data stories differ from traditional storytelling and how to purposefully craft a compelling data story, but also how to employ the horsepower of Tableau to structure data analysis projects so that they can effectively analyze, visualize, and communicate insights in a way that is meaningful for stakeholders across a variety of communication mediums.
Biographie:
Lindy Ryan is passionate about telling stories with data. She specializes in translating raw data into insightful stories through carefully curated visuals and engaging narrative frameworks.
Before joining academia, Lindy was the Research Director for research and advisory firm Radiant Advisors from 2011 through 2016. In this role Lindy led Radiant’s analyst activities in the confluence of data discovery, visualization, and visual analytics. She also developed the methodology for the Data Visualization Competency Center (DVCC), a framework for helping data-driven organizations to effectively implement data visualization for enterprise-wide visual data analysis and communication. Her tool-agnostic approach has been successfully implemented at a variety of organizations across several industries and with multiple visualization technologies, including Tableau, Qlik, and GoodData. She remains a respected analyst in the data visualization community and is a regular contributor to several industry publications as well as a speaker at conferences worldwide.
Lindy began her academic career as an associate faculty member at City University of Seattle’s School of Applied Leadership where she taught graduate courses in business leadership from 2012 to 2016. In early 2016 she joined the ambitious team at the Rutgers Discovery Informatics Institute and began contributing to multidisciplinary research focused on designing solutions for the next generation of supercomputers tasked with enabling cutting-edge extreme-scale science. Currently, Lindy leads RDI2’s research on understanding and preventing cyberbullying behaviors in emerging technology users through advanced computing approaches.
Today, Lindy teaches courses in visual analytics and data visualization in Rutgers University’s Professional Science Masters program and in Montclair State University’s Business Analytics program. She is a recipient of the MSU Professing Excellence Award, which recognizes professors’ teaching excellence, particularly those who inspire and motivate students. This honor is especially meaningful to Lindy because in addition to her passion for teaching, her research includes a commitment to STEM advocacy, and she spends time on research related to increasing gender equity in CS&E and finding new and novel ways to nurture visual data literacy skills in early STEM learners.
Lindy is an active committee member of the New Jersey Big Data Alliance, a partnership of New Jersey-based academic institutions that serves as the State’s legislated consortium on research, education and outreach in advanced computation and big data. She is the author of The Visual Imperative: Creating a Culture of Visual Discovery released by Morgan Kaufmann in 2016, and the owner of Black Spot Books, a traditional, analytics-driven small-press publishing house.
Learn more about Lindy at www.visualdatastorytelling.com. You can also follow her on Twitter @lindy_ryan or view samples of her work on her Tableau Public page at https:// public.tableau.com/profile/lindyryan#!/.
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