26 Self-Discovery: Data Visualization Skills
How to use these tables:
- Read the description of each skill and make your best estimate of your current level of ability based on the following scale:
- Aware: You are brand new to this skill. You may know about it conceptually, but have not yet completed the task yourself.
- Learner: You’re just to learn this skill or still rely on detailed instructions and guides to complete this task.
- Skilled: You have some ability in this area, but you still need assistance or to tackle certain parts or advanced aspects.
- Expert: You confidently handle challenges in this topic area, do not need support, and can clearly and simply explain concepts to others.
- Strategist: You are applying this technique in new ways and creating new ways of doing this, you are able to mentor/guide intermediates and advanced individuals in this skill.
- Optional: Determine if there are any skills for which you would like to have a different future skill level and indicate your desired level. Keep in mind, that your desired skill levels may change over time and may change as you consider different possible career options. You will likely come back to this table and change your desired levels many times.
Note. Don’t worry too much about where you rate yourself, there’s no true score or measurement for something like this. The scale provided is only meant to provide a general sense of guidance and to serve as a thought provoking exercise.
Data Visualization Skills
| Skill | Description | Current Level (Aware/Learner/ Skilled/Expert/Strategist) | Desired Level (Aware/Learner/ Skilled/Expert/Strategist) |
| Chart Types & Techniques | Master various chart types and techniques, including bar charts, line charts, scatter plots, histograms, heatmaps, tree maps, bubble charts, and more. | ||
| Visual Data Exploration & Analysis | Develop proficiency in selecting the most effective visualizations for different data analysis techniques that best highlight insights and patterns in the data. (e.g., scatterplot for identifying if non-linear relationships are present) | ||
| Visual Data Cleaning | Apply your data visualization skills to support cleaning and preprocessing of data to ensure data accuracy and prepare it for visualization. (e.g., a scatterplot may quickly show an erroneous outlier that needs to cleaned.) | ||
| Visual Design Principles | Understanding of core design principles like color theory, composition, white space, and hierarchy. | ||
| Accessible Data Visualization Design | Incorporating accessibility best practices. | ||
| Scorecards & Dashboards | Design and build scorecards & dashboards that present key metrics and performance indicators in a clear and concise way. Includes layout design, reporting tool use, and interactive components where applicable. | ||
| Animated Visualizations | Use animation techniques to enhance your data visualizations and make them more engaging and impactful. | ||
| Storytelling | Create a narrative that captures the audience’s attention, conveys insights clearly, and leaves a lasting impression. Encompasses knowing the audience, crafting compelling visuals, titles, labels and guiding viewers through the data journey with a well-defined message. | ||
| Data Visualization Tools | Ability in one or more data visualization tools such as Tableau, Power BI, QlikView, Google Data Studio, matplotlib, seaborn, ggplot, etc. | ||