Communicating with Data - Helion

ebook

Autor: Carl Allchin
ISBN: 9781098101817
stron: 340, Format: ebook
Data wydania: 2021-10-01
Księgarnia: Helion

Cena książki: 211,65 zł (poprzednio: 246,10 zł)
Oszczędzasz: 14% (-34,45 zł)

Osoby, które kupiły tę książkę, wybierały także »

Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.

Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once both your business and data experts possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization.

Learn the fundamental data skills required to work with data
Use data visualization to influence change in your organization
Learn how to apply data techniques to effectively work with data end to end
Understand how to communicate data points clearly and persuasively
Appreciate why different stakeholders often have divergent needs and views
Create a playbook for using data with different departments

Osoby które kupowały "Communicating with Data", wybierały także:

Windows Media Center. Domowe centrum rozrywki 66,67 zł, (8,00 zł -88%)
Ruby on Rails. Ćwiczenia 18,75 zł, (3,00 zł -84%)
DevOps w praktyce. Kurs video. Jenkins, Ansible, Terraform i Docker 190,00 zł, (39,90 zł -79%)
Przywództwo w świecie VUCA. Jak być skutecznym liderem w niepewnym środowisku 58,64 zł, (12,90 zł -78%)
Scrum. O zwinnym zarządzaniu projektami. Wydanie II rozszerzone 58,64 zł, (12,90 zł -78%)

Spis treści

Communicating with Data eBook -- spis treści

Preface
- Why I Wrote This Book
- Who Is This Book For?
- How the Book Is Organized
- Conventions Used in This Book
- OReilly Online Learning
- How to Contact Us
- Acknowledgments
I. Communication and Data
1. Communication
- What Is Communication?
  - The Communication Process
  - Getting Through to Your Audience: Context and Noise
  - Dont Forget About Memory
- Why Visualize Data?
  - Pre-Attentive Attributes in Action
  - Unique Considerations
- Summary
2. Data
- What Is Data?
  - Key Features of Data
  - Rows and Columns
    - Rows
    - Columns
  - Data Types
    - Numbers
    - Strings
    - Dates
    - Booleans
- How Is Data Created?
  - Where Is Data Created?
    - Operational systems
    - Surveys
    - Movement/transportation
    - The Internet of Things
  - Should You Trust Your Data?
- Data as a Resource
  - Files
    - Common file types
    - Common challenges
  - Databases, Data Servers, and Lakes
    - Common types of databases
    - Common challenges
  - Application Programming Interfaces
  - Data Security and Ethics
- Easy or Hard? The Right Data Structure
  - The Shape of Data
    - Categorical data
    - Measures
    - Pivotcolumns to rows
    - Pivotrows to columns
    - Aggregation
  - Cleaning Data
    - Splitting
    - Replacing rogue characters
- The Right Data
  - Requirement Gathering
    - Asking the right questions
    - Sketching
  - Use of the Data
    - Frequency
    - Volume
    - One big data set versus many
- Summary
II. The Elements of Data Visualization
3. Visualizing Data
- Tables
  - How to Read Tables
    - Categories
    - Measures
  - How to Optimize Tables
    - Highlight tables
  - When You Might Not Use Tables
- Bar Charts
  - How to Read Bar Charts
    - Axis
    - Zero line
    - Headers
  - How to Optimize Bar Charts
    - Multiple categories
    - Color
    - Histogram
    - Percentage-of-total charts
    - Waterfall charts
  - When You Might Not Want to Use Bar Charts
- Line Charts
  - How to Read Line Charts
  - How to Optimize Line Charts
    - Cycle plots
    - Slope charts
    - Sparklines
    - Area charts
  - When You Might Not Use Line Charts
- Summary
4. Visualizing Data Differently
- Chart Types: Scatterplots
  - How to Read Scatterplots
    - Multiple axes
    - Plots
    - Color
    - Shapes
  - How to Optimize Scatterplots
    - Small multiple scatterplots
    - Quadrant charts
  - When to Avoid Scatterplots
    - Too many colors
    - Nondifferentiable color palettes
- Chart Types: Maps
  - How to Read Maps
    - Size and shape
    - Choropleth maps and color
  - How to Optimize Maps
    - Tile maps
    - Data thresholds
    - Density and hex bin maps
  - When to Avoid Maps
- Chart Types: Part-to-Whole
  - How to Read Part-to-Whole Charts
    - Sections
    - Angles
    - Labels
    - Donut charts
    - Treemaps
  - When to Use Part-to-Whole Charts
  - When to Avoid Part-to-Whole Charts
- Summary
5. Visual Elements
- Color
  - Types of Color Palettes
    - Hue
    - Intensity: Sequential color palettes
    - Intensity: Diverging color palettes
  - Choosing the Right Color
    - Theme
    - Limitations to the effectiveness of color
  - Avoiding Unnecessary Use of Color: Double Encoding
- Size and Shape
  - Themed Charts
    - Scatterplots
    - Unit charts
  - Size and Shape Challenges
    - Scaling
    - Different devices
    - Unsquare shapes
    - Limitation of uses
- Multiple Axes
- Reference Lines/Bands
  - Reference Lines
  - Reference Bands
- Totals/Summaries
  - Totals in Tables
    - Column totals
    - Row totals
    - Subtotals
  - Totals in Charts
- Summary
6. Visual Context
- Titles
  - Main Title
  - Subtitles, Standfirsts, and Chart Titles
- Text and Annotations
  - Annotations
  - Text Boxes
  - Text Formatting
    - Text font
    - Text size
- Contextual Numbers
- Legends
  - Shape Legends
  - Color Legends
    - Hue
    - Sequential (intensity)
    - Diverging
    - No legend
  - Size Legends
- Iconography and Visual Cues
  - Thematic Iconography
  - Audience Guidance
- Background and Positioning
  - The Z Pattern
  - Whitespace
- Interactivity
  - Tooltips
    - Descriptions
    - Extra data points
    - Charts
  - Interactions
    - Highlighting
    - Filtering
- Summary
7. The Medium for the Message: Complex and Interactive Data Communication
- Explanatory Communications
  - Gathering Requirements
  - Updating Data in Explanatory Views
  - So What?
- Exploratory Communications
  - Gathering Requirements
  - Flexibility and Flow
- Methods: Dashboards
  - Monitoring Conditions
  - Facilitating Understanding
    - Context
    - Answering multiple questions
- Methods: Infographics
- Methods: Slide Presentations
- Methods: Notes and Emails
- Summary
III. Deploying Data Communication in the Workplace
8. Implementation Strategies for Your Workplace
- Tables Versus Pretty Pictures
  - Data Culture
    - Data-driven leadership
    - Investment in data tools
    - Communication
  - Data Literacy
  - Improving the Visualization Mix
    - Start with the basics
    - Instructing your users
- Static Versus Interactive
  - Lets Talk About PowerPoint
  - More Than Just PowerPoint
    - Easier production
    - Easier to use
    - Easier data storage
  - Interactive User Experience
- Centralized Versus Decentralized Data Teams
  - The Data Team
  - Data Sources
  - Reporting
  - Pooling Data Expertise
    - Analyst community
    - Tool expertise
    - Knowledge of the data
  - Self-Service
- Live Versus Extracted Data
  - Live Data
  - Extracted Data Sets
- Standardization Versus Innovation
  - Importance of Standardization
  - Importance of Innovation
- Reporting Versus Analytics
  - Reporting: Mass Production
  - Analytics: Flexibility but Uncertainty
- Finding the Perfect Balance
- Summary
9. Tailoring Your Work to Specific Departments
- The Executive Team
- Finance
- Human Resources
- Operations
- Marketing
- Sales
- Information Technology
- Summary
10. Next Steps
- Step 1: Get Inspired
- Step 2: Practice
- Step 3: Keep Reading
Index