Data visualisation VISL
Facilitating understanding of data by displaying concepts, ideas and facts using graphical representations.
Revision notes
Updates for SFIA 9
- Theme(s) influencing the updates for this skill: Continued refinement for data and analytics skills, Making SFIA easier to consume (enhance readability/guidance/descriptions), Making SFIA easier to consume (new levels).
- New level 2 added to support entry-level roles.
- Readability improvements have been made to levels 3, 4, and 5.
- You can move to SFIA 9 when you are ready - SFIA 8 skill descriptions will still be available to use.
- Previous SFIA assessments or skills mapping are not impacted by this change.
Guidance notes
Activities may include, but are not limited to:
- condensing and encapsulating data characteristics, making it easier to surface opportunities, identify risks, analyse trends and drive effective decision-making
- presenting findings and data insights in creative ways to facilitate the understanding of data across a range of technical and non-technical audiences
- developing narratives and storytelling around data to enhance understanding and support decision-making.
The skill is typically put into practice by using specialist analytics tools. Specialisation in this skill implies a requirement to use more than just standard office software to create graphical representations of simple data.
Understanding the responsibility levels of this skill
Where lower levels are not defined...
- Specific tasks and responsibilities are not defined because the skill requires a higher level of autonomy, influence, and complexity in decision-making than is typically expected at these levels. You can use the essence statements to understand the generic responsibilities associated with these levels.
Where higher levels are not defined...
- Responsibilities and accountabilities are not defined because these higher levels involve strategic leadership and broader organisational influence that goes beyond the scope of this specific skill. See the essence statements.
Developing skills and demonstrating responsibilities related to this skill
The defined levels show the incremental progression in skills and responsibilities.
Where lower levels are not defined...
You can develop your knowledge and support others who do have responsibility in this area by:
- Learning key concepts and principles related to this skill and its impact on your role
- Performing related skills (see the related SFIA skills)
- Supporting others who are performing higher level tasks and activities
Where higher levels are not defined...
- You can progress by developing related skills which are better suited to higher levels of organisational leadership.
Click to learn why SFIA skills are not defined at all 7 levels.
Show/hide extra descriptions and levels.
Levels of responsibility for this skill
2 | 3 | 4 | 5 |
Level 1
Data visualisation: Level 2
Creates standard data visuals using established products, tools and techniques, under routine supervision.
Assists in updating and refining existing data visualisations to maintain effective representation of concepts, ideas and facts.
Data visualisation: Level 3
Uses visualisation products, as guided, to design and create data visuals.
Selects appropriate visualisation techniques from the options available.
Engages with the target user to prototype and refine specified visualisations.
Assists in developing narratives around data sets to support understanding and decision-making.
Data visualisation: Level 4
Applies a variety of visualisation techniques and designs the content and appearance of data visuals.
Operationalises and automates activities for efficient and timely production of data visuals.
Selects appropriate visualisation approaches from a range of applicable options. Develops narratives around data sets to guide decision-making processes and enhance understanding of key insights.
Contributes to exploration and experimentation in data visualisation.
Data visualisation: Level 5
Leads exploration of new approaches for data visualisation. Establishes the purpose and parameters of the data visualisation.
Oversees the use of data visualisation tools and techniques. Communicates results using appropriate methods for the target audience.
Advises on the use of data visualisation approaches for different purposes and contexts to satisfy requirements. Develops plans to meet user needs.
Collaborates with stakeholders to identify key insights and create compelling narratives that effectively communicate the story behind the data to drive decision-making processes.