Documentation: Data Visualisation 📈🤕

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Creator: Stephen Alger C16377163 DT228/4
Process Documentation: Data Visualisation.
Module: Visualising Data CMPU4091
Date: January 2021

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Below are the Weekly Updates & Key Takeaways:

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Week One: Introduction 👋

Lecture Notes: Available Here.

• 🎯 Primary Module Aim: The central aim of this module is help students attain the ability to take complex data, process it and extract value from it through visualisation.

• 🤔 Consider The Problem We are not machines; The unimaginably vast arrary of arbitrary data sets that exist are completely beyond our comprehension - Every single computer interaction leaves a data trail, from the exact moment and amount of a Visa Card payment to the constant, precise recording of each Dublin Bus GPS position. It all leaves a data trail. Eventually someone needs to package this data mess into bus timetables, actionable insights or quarterly spending reports. The adage "If you can't measure it, you can't manage it" holds true here more than anywhere.

• 🤨 Functions of Visualisations?

  • Record: store information.
  • Analyze: support reasoning about information.
    • Process and calculate
    • Reason about data
    • Feedback and interaction
  • Communicate: convey information to others.
    • Share and persuade
    • Collaborate and revise
    • Emphasize important aspects of data

• 📝 Why Do We Need Visualisation?

  • The challenge is to create effective and engaging visualizations that are appropriate to the data.

  • Well-designed visual representations can replace cognitive calculations with simple perceptual inferences and improve comprehension, memory, and decision making.

  • By making data more accessible and appealing, visual representations may also help engage more diverse audiences in exploration and analysis

• 🔨 Building Effective Visualisation Incorporate the Following:

  • Perceptual Psychology
  • Cognitive Science
  • Graphic Design
  • Visual art

• 🔧 Software Tools available?

  • Jupyter 🪐
  • Tableau Public 📊
  • R Programming & Visualisations 🧑‍💻

• End of Lecture;

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📁 Lab Notes:

• The Big Idea, Elevator Pitch & The Three Minute Story.
• It's Far Easier to Tell a rambling spiel, the art is in the well crafted, clear & concise call to action
• “I would have written a shorter letter, but I did not have the time” - Blaise Pascal

💡 The Big Idea? What is it?

1. Articulate your Point of View.
2. Convey What is at Stake to the Audience should they accept or decline.
3. And; It must be a complete sentence, nothing more nor less.

• So What is the point of this exercise? Illustrating the value of making your concept universally understandable. Much like will will try to make our Data accessible through Visualisation going forward.

📄 Lab Assignment: Procure your own 'Big Idea' 💭

🔖 My Lab Work/ Group Work Submission: The Big Idea PDF.

📚 Futher Reading: : The 3 Minute Story - StoryTellingWithData.com.

End of Lab;

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Week Two:

Lecture Notes:

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Lab Notes:

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