Welcome to the world of data visualisation, where raw data transforms into compelling visual narratives. In this blog post, we’ll explore the “10 Steps in Data Visualisation” to help you turn complex data into clear, actionable insights. Whether you’re a seasoned data analyst or just starting. These steps will guide you through the process of creating visuals that not only inform but also captivate your audience. Let’s dive in and unlock the power of data visualisation together!

Image by Hancock Creative

1.  KNOW YOUR AUDIENCE

Confirm who will be reading your data and how this data will be understood, ensure that the level of detail you go into meets the needs and expectations of your required audience.  Key questions to ask yourself:

•   Who is your audience?
•   What is your audience’s numeracy level?
•   How familiar is your audience in data visualisations?
•   How much time does your audience have?
•   What types of decisions can your audience make?    

2.  DECIDE THE QUESTIONS

Confirm the types of questions you want to answer during the analysis process and the ultimate goal of this process remembering to keep an open mind to the final result. General reasons for data analysis include:

•   Market Research
•   Product Research
•   Social Media Research
•   Website Research
•   Customer Research
•   Financial Research

3.  COLLECT THE DATA

Decide on what data is going to be used to analyse and what data will be able to answer the questions you have confirmed in step 2 above.  Data could be collected from different areas including:

•   System Databases
•   Financial Systems
•   Surveys
•   Google Analytics
•   Website Traffic

Image by Xaltius Tech

4.  CLEAN THE DATA

Work on transforming the data into a format that enables easier analysis and visualisations.  This could involve the following:

•   Converting the style of your data (Vertical data set to Horizontal)
•   Renaming your headings
•   Filling in any empty cells
•   Converting to correct formats (date format, number format)

5.  IMPORT THE DATA

Import the data into your Business Intelligence Tool to effectively start the analyses process.  Business Intelligence Tools can include the following:

•   Tableau Desktop or Public
•   Microsoft Power BI
•   Google Data Studio
•   Microsoft Excel

6.  EVALUATE THE DATA

Explore the data set by creating exploratory visualisations to identify the following:

•   Key patterns found in the data
•   Certain trends found in the data
•   Errors showing up in the data
•   Anomalies or unusual results found in the data

7.  CREATE VISUALISATIONS

Start to create different types of visualisations to help identify key trends that answer your goals set out in step 1 of the analysis process.  Different types of visualisations include the following:

•   Scatter Plot Graph – Great to determine any missing data or anomalies found in the data set.
•   Bar Graph – The most effective and understood visualisation used to compare categorical data over a continuous variable.
•   Line Graph – Great if you have a timeline in your data set and you want to see the trend over time.
•   Geometric Maps – Great if you have a location in your data set and you want to see the trend over countries, cities or towns.  

Image by Inspiration Feed

8.  USE COLOUR THEORY

Select the right colour scheme of your visualisation but ensure the colours are consistent throughout the different visualisations.

•   Use one colour to represent continuous data. 
•   Use contrasting colours for comparison data.
•   Use colours that are found in nature as people respond better to colours they see everyday.
•   Use your brand colours for marketing presentations.
•   Use colour to highlight the key information that the viewers should be focusing on.
•   Remember to use colours that can also be seen if your viewers are colour blind.

Image by Data Labs Agency

9.  DESIGN YOUR STORY

Presenting your data as a story helps engage the audience and allows you to inform your audience and encourage your audience to take specific actions. Key elements of storytelling using data visualisation include:

• Understanding the Context – Focus on explanatory analysis and communication and answer the following questions:
  •   Who are you communicating to?
  •   What do you want your audience to know or do?
  •   How can you use data to help make your point?
•   Select an Effective Visualisation – Choose the right visualisation that will get your point across in a simple but understandable way.
•   Draw attention where you want it – Engage your audience in the story by focusing on the key information you want your audience to know.

10.  PRESENT YOUR ANALYSIS REPORT

Tell your story by representing it in a report, presentation or interactive dashboard by engaging your audience emotionally.  Key things to remember when telling your story using data visualisations:

•   Keep the story simple but effective
•   Be authentic when explaining the story
•   Communicate the story to your audience – remember that the story is for them not you.

Data visualisation isn’t just about creating beautiful charts and graphs. It’s about unlocking the true potential of your data to drive informed decisions and tell meaningful stories. By following these 10 steps, you’ll be well-equipped to transform raw data into powerful visual insights that resonate with your audience.

If you’re eager to dive deeper into the world of data visualisation or need personalised assistance with your projects. Don’t hesitate to reach out to learn more and start a conversation. Let’s harness the power of data together and take your visuals to the next level!