1. Data visualization: who and what?
Welcome to the course Data Visualization in KNIME.
They say that a picture is worth a thousand words.
It is a mantra that everyone who works with data knows well. And with data visualization techniques, you can make it true.
2. Data exploration
Data visualization can have two scopes: exploration or explanation.
Data exploration is the task of discovering what the data has to tell. You examine patterns, relations, and trends of unknown data to understand what they can reveal.
3. Data explanation
On the other hand, data explanation usually comes later in the process, aiming to communicate to other people what you have discovered. The data might contain some interesting facts, and you use data visualization methods to convey them.
4. Tabular data
Whether exploring data or preparing a report to communicate your findings, tabular data might already be effective.
For example, this table shows that the product that was bought the most was the water bottle.
5. Tabular data
However, as the data increases in size and complexity, it becomes harder to understand what it is trying to tell us.
What is the product that sold the most between the two stores?
6. Charts to reveal patterns
Creating a chart out of your data helps make the message more explicit.
7. Advantages
Moving from a tabular data representation to a chart gives you a new perspective on the data, which can unlock new insights. For example, you can see the distribution of your data, compare different variables, explore relationships and correlations between variables, detect outliers, visualize trends in time and space, and so on.
8. Audience
However, before exploring the data and focusing on the message you want to communicate, you need to consider who you are communicating to.
In other words, the audience of your visualization.
Are they already familiar with the data?
How much background information do they already have?
What specific insights are they expecting?
How many details do they need?
How familiar are they with the data visualization techniques?
9. Set the scene
Those were a lot of questions; let's try to give some answers and set the scene for this course's example.
The data we are using contains information about your company's CO2 emissions.
You have information about the employees' commuting and energy usage during the last year.
10. Set the scene
First, you want to perform an exploratory analysis, creating different plots to learn more about the data.
Then, we group the visualizations in a dashboard so that the company's board members can understand the key findings and take action.
11. Let's practice!
Before digging into the data, recap what you have learned so far in an exercise.