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Data Visualisation principals and Practice in under one Hour
Rating: 4.4 out of 5(20 ratings)
598 students

Data Visualisation principals and Practice in under one Hour

Learn Quick Principals, limitations and benefits of data visualisation principals for most used charts in just an hour
Created byManish Gupta, TA eHMS
Last updated 7/2023
English
English [Auto],

What you'll learn

  • Principals of Data Visuation
  • When to use and not to use key Charts
  • Sample how to create these charts
  • practical problems

Course content

2 sections • 22 lectures • 1h 4m total length

  • Introduction to the course4:14

    Identify data type (integer, real, categorical, time series, geospatial), decide the story (relationship, comparison, composition, distribution, or trend), and consider the user to choose the right chart.

  • Data Visualisation Process in Excel2:37

    Explore Excel data visualizations from normal tables with formulas requiring manual updates to pivot tables with automatic refresh, then Power Pivot for data models across multiple sources.

  • Process of Data Visualisation8:12

    Collect data from ERP, Excel, PDFs, websites, and live streams; clean and format it, then create charts and dashboards with calculated columns and VLOOKUPs.

  • Key Principals of Data Visualisation4:32

    Prioritize clarity and simplicity to convey a single message per chart, build a focused narrative, and avoid noise by curating data points and using design that supports the story.

  • Formatting principals (Color)0:37

    Apply color formatting for charts using two to three colors, with shades for similar items, gray for insignificant categories, and keep variables blank while using complementary colors for distinct groups.

  • Formatting Principals (Clarity)0:35

    Enhance clarity by removing nonessential elements like data points and grid lines, keep the title important, limit color, and ensure charts are left aligned from left to right.

  • Examples of Good Charts1:09

    Explore good charts that communicate clearly with minimal information, using revenue, pricing, and profit indicators alongside a dashboard and area chart to show trends and high accident risk.

  • Examples of Bad Charts1:14

    Examine why bad charts mislead, from too many variables on line charts to improper pie charts for monthly sales. Learn when to use bar or line charts for clear trends.

  • Examples of Ugly Charts2:22

    Explore examples of ugly charts and learn to avoid misused axes that distort data. See how non-zero starting points and misleading visuals can misrepresent financial figures.

Requirements

  • Basic understanding of excel

Description

Data visualization is a crucial skill for professionals working with data in various fields, and Excel provides a powerful platform for creating visually appealing and informative charts. In this comprehensive course, we will dive deep into the world of data visualization using Excel charts, covering a wide range of chart types, including bar charts, line charts, pie charts, histograms, treemaps, and more.

Throughout the course, you will learn the fundamental principles of data visualization and how to effectively represent data using different chart types. We will explore the purposes and use cases of each chart type, helping you understand when to utilize a specific chart to showcase different types of data, such as comparing values, identifying trends over time, displaying proportions, or analyzing distribution patterns.

You will gain hands-on experience in creating, customizing, and formatting various charts using Excel's intuitive interface. We will cover essential techniques for enhancing the visual impact of your charts by applying appropriate color schemes, labels, legends, and annotations. Moreover, we will delve into advanced features like adding trendlines, error bars, and data labels to provide deeper insights into your data.

Additionally, we will discuss best practices for effective data visualization, including principles of design, data storytelling, and ensuring clarity and accuracy in presenting information. You will also learn how to create interactive dashboards using slicers and sparklines, allowing you to filter and dynamically update your charts based on user inputs.

By the end of this course, you will have a solid foundation in data visualization using Excel charts, enabling you to confidently present your data in visually compelling ways. Whether you are a business analyst, financial professional, researcher, or data enthusiast, this course will equip you with the skills and knowledge to transform raw data into impactful visual representations that drive understanding and decision-making.

Who this course is for:

  • finance professionals who need to learn basics of data visualisation

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