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Record Nr. |
UNINA9910816467103321 |
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Autore |
Yuk Mico |
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Titolo |
Data visualization for dummies / / by Mico Yuk, Stephanie Diamond |
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Pubbl/distr/stampa |
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Hoboken, New Jersey : , : John Wiley & Sons, Incorporation, , 2014 |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (258 p.) |
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Collana |
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--For dummies Data visualization for dummies |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Information visualization - Data processing |
Data analysis |
Information visualization |
Quality control |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Contents at a Glance; Table of Contents; Introduction; Part I: Getting Started with Data Visualization; Chapter 1: Introducing Data Visualization; Understanding Data Visualization; Recognizing the Traits of Good Data Viz; Embracing the Design Process; Ensuring Excellence in Your Data Visualization; Chapter 2: Exploring Common Types of Data Visualizations; Understanding the Difference between Data Visualization and Infographics; Picking the Right Content Type; Appreciating Interactive Data Visualizations; Observing Visualizations in Different Fields; Using Dashboards; Discovering Infographics |
Chapter 3: Knowing What You Must about Big Data Defining Big Data; Seeing How Big Data Changes Business; Avoiding Dying by Tool Choice; Part II: Mastering Basic Data Visualization Concepts; Chapter 4: Using Charts Effectively; Deciding Which Charts to Use and When to Use Them; Dipping Into Less-Common Charts; Chapter 5: Adding a Little Context; Making Text Useful; Exploring Text Analysis; Chapter 6: Paying Attention to Detail; Uncovering How People Digest Data; Presenting Common Visual Patterns; Deciding to Use a Template; Achieving Consistency across Devices |
Part III: Building Your First Data Visualization Chapter 7: Defining an Easy-to-Follow Storyboard; Business Intelligence Overview; Delving Into |
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Your Story; Building Your First Storyboard; Chapter 8: Developing a Clear Mock-Up; Getting Started with Your Mock-Up; Building Template Layouts; Chapter 9: Adding Effective Visuals to Your Mock-Up; Recognize the Three Traits of an Effective Visual; Focus on Insight, Not Hindsight; Add Visuals to Your Mock-Up; Chapter 10: Adding Functionality and Applying Color; Recognizing the Human Components; Dipping Into Color |
Chapter 11: Adding Some Finishing Touches Choosing Useful Links; Adding Legal Stuff; Discovering Visual Cues; Adding Location Intelligence; Chapter 12: Exploring User Adoption; Understanding User Adoption; Considering Five UA Measurements; Marketing to Data Viz Users; Part IV: Putting Data Viz Techniques into Practice; Chapter 13: Evaluating Real Data Visualizations; Analyzing Data Visualizations by Category; Evaluating Data Visualizations; Chapter 14: Recognizing Newbie Pitfalls; Going Overboard with Data; Falling into the One-Shoe-Fits-All Trap; Focusing on the Tool Instead of the Story |
Building Mobile Last Abusing Pie Charts; Using Green for Alerts; Ignoring Basic Statistics; Not Mastering User Engagement; Part V: The Part of Tens; Chapter 15: Top Ten Data Visualization Resources; Edward Tufte; Visually; The Functional Art; Visualizing Data; Chart Porn; The Excel Charts Blog; Flowing Data; Data visualization.ch; GE Data Visualization; #dataviz and #bigdata; Chapter 16: Top Ten Fears of New Data-Viz Creators; Telling the Wrong Story; Creating an Ugly Data Viz; Picking the Wrong Things to Measure; Alienating Other Stakeholders; Misunderstanding the Audience for Your Data Viz |
Forgetting about Copyrights and Legal Matters |
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Sommario/riassunto |
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A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers |
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