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Visual Analytics for Dashboards [electronic resource] : A Step-by-Step Guide to Principles and Practical Techniques / by Arshad Khan.

By: Contributor(s): Material type: TextPublisher: Berkeley, CA : Apress : Imprint: Apress, 2024Edition: 1st ed. 2024Description: XXIII, 174 p. 82 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9798868801198
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • QA76.9.Q36
Online resources:
Contents:
Chapter 1: Dashboards -- Chapter 2: Scorecards -- Chapter 3: Key performance indicators -- Chapter 4: Dashboard requirements -- Chapter 5: Dashboard design -- Chapter 6: Data visualization -- Chapter 7: Visualization principles -- Chapter 8: Visual communication -- Chapter 9: Understanding and using charts -- Chapter 10: Selecting charts -- Chapter 11: Best Practices and Tips.
In: Springer Nature eBookSummary: This book covers the key principles, best practices, and practical techniques for designing and implementing visually compelling dashboards. It explores the various stages of the dashboard development process, from understanding user needs and defining goals, to selecting appropriate visual encodings, designing effective layouts, and employing interactive elements. It also addresses the critical aspect of data storytelling, examining how narratives and context can be woven into dashboards to deliver impactful insights and engage audiences. Visual Analytics for Dashboards is designed to cater to a wide range of readers, from beginners looking to grasp the fundamentals of visual analytics, to seasoned professionals seeking to enhance their dashboard design skills. For different types of readers, such as a data analyst, BI professional, data scientist, or simply someone interested in data visualization, this book aims to equip them with the knowledge and tools necessary to create impactful dashboards. What you’ll learn The principles of data visualization How to create effective dashboards Meet all the requirements for visual analytics/data visualization/dashboard courses Deepen understanding of data presentation and analysis How to use different kinds of tools for data analysis, such as scorecards and key performance indicators .
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Chapter 1: Dashboards -- Chapter 2: Scorecards -- Chapter 3: Key performance indicators -- Chapter 4: Dashboard requirements -- Chapter 5: Dashboard design -- Chapter 6: Data visualization -- Chapter 7: Visualization principles -- Chapter 8: Visual communication -- Chapter 9: Understanding and using charts -- Chapter 10: Selecting charts -- Chapter 11: Best Practices and Tips.

This book covers the key principles, best practices, and practical techniques for designing and implementing visually compelling dashboards. It explores the various stages of the dashboard development process, from understanding user needs and defining goals, to selecting appropriate visual encodings, designing effective layouts, and employing interactive elements. It also addresses the critical aspect of data storytelling, examining how narratives and context can be woven into dashboards to deliver impactful insights and engage audiences. Visual Analytics for Dashboards is designed to cater to a wide range of readers, from beginners looking to grasp the fundamentals of visual analytics, to seasoned professionals seeking to enhance their dashboard design skills. For different types of readers, such as a data analyst, BI professional, data scientist, or simply someone interested in data visualization, this book aims to equip them with the knowledge and tools necessary to create impactful dashboards. What you’ll learn The principles of data visualization How to create effective dashboards Meet all the requirements for visual analytics/data visualization/dashboard courses Deepen understanding of data presentation and analysis How to use different kinds of tools for data analysis, such as scorecards and key performance indicators .

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