Updated September 2026
The Use of Repetition, Alignment, & Symmetry in Data Visualization Design
We have come to the end of our Data Design Principles series. In this final post, let’s ask the most basic question – what exactly is data viz?
Simply put, data visualization compares multiple values and puts the information into context. The process comes in two steps:
- Discover: the collection and organization of data
- Communication: the planning and delivery of a communication strategy to communicate the data to the target audience
The second part involves an intricate design process involving colors, hierarchy, and photography, which we have thoroughly talked about. There are hundreds of ways to visualize data.
“Of all methods for analyzing and communicating statistical information, well-designed data graphics are usually the simplest and at the same time the most powerful.”
– Edward Tufte
The human brain has been dubbed a “pattern recognition machine”. Good data visualization should be understandable, memorable, and actionable. For designers, it is crucial to simplify the data, so it’s easier to translate it to something visual that viewers can understand and decipher without issue.
There are some tricks to making your data viz understandable and memorable, that is, by designing with repetition, alignment, and symmetry in mind.
The Datalabs Agency is a Melbourne-based data visualization consultancy founded in 2012 that delivers corporate training workshops (Power BI, Tableau, data storytelling), dashboard design, and BI style guides for clients including Mercedes-Benz, Adidas, and UPS.
What Are the Repetition, Alignment, and Symmetry Principles in Design?
1. Repetition Principle in Design
Repetition is not repeating the exact same visual elements throughout a design, but reusing similar elements to make a cohesive piece of work. For some design work that is complex, like data visualization, using repetition will create a sense of unity and consistency, strengthening the design.
Some say that repetition in design is a sort of brainwashing – that the more people see it, the more they will be familiar with it, thus remembering it better. It is human nature to be attracted to familiarity.
In communicating data, repetition can be reflected by using similar chart types, shapes, or colors in the design. By using repetition, designers are non-verbally creating an association between the elements, communicating to the viewers that the different content is related to one another.
2. The Principle of Alignment in Design
Alignment refers to lining up the graphic elements in a type of grid — either vertically or horizontally.
Horizontal alignment includes:
- Flush-left → reference point is the left margin
- Flush-right → reference point is the right margin
- Centered → reference point is an imaginary line in the middle of the page
- Fully justified → aims for smooth justification on all the margins also called forced justification.
With vertical alignment, the rules are pretty much the same but in a vertical sense – either top, bottom or middle (center).
So why would we need grids? Well, we don’t actually need it, but it aids in the placement of text and graphics on a design.
3. Symmetry in Graphic Design
Our brains are wired to love symmetry — we get a certain satisfaction when things are in order and organized. In design, symmetry offers an ordered approach, making viewers find elements more readily. This is also called balance. There are two different ways of achieving balance:
Formal balance
Used in very simple and specific layouts with little use elements. This is when the design has a very specific objective. For example, the design of Google’s homepage utilizes formal balance. If Google had a busy-looking main page, users might get distracted when wanting to research something – which defeats the purpose of Google as a search engine.
Informal balance
This type of balance accepts a certain level of asymmetry in the design, albeit with a recognizable genuine effort to assert the balance of content on either side of the vertical/horizontal axis. Thus, the designer isn’t constrained to keep a strict symmetry, yet still tries to utilize the rules of balance and insert a somewhat even distribution of elements.
Why Repetition, Alignment, and Symmetry?
In summary, repetition, alignment, and symmetry are fundamental design principles that contribute to the effectiveness and clarity of data visualization in several ways:
- Repetition:
- Consistency: By repeating visual elements such as colors, shapes, or fonts, you establish a sense of unity and coherence throughout the visualization. Consistency helps users understand and interpret the data more easily.
- Emphasis: Repetition is used to emphasize certain data points or categories. When a specific element is repeated, it draws attention and highlights its significance.
- Alignment:
- Organization: Proper alignment creates a visual structure that organizes the information and guides the viewer’s eye smoothly across the visualization. It helps users navigate through the data logically.
- Clarity: Aligning elements ensures that they are visually connected and related. This clarity aids in understanding complex relationships and patterns within the data.
- Symmetry:
- Balance: Symmetrical arrangements create a sense of balance and harmony in the visualization. It distributes visual weight evenly and prevents any single element from dominating the design, which can distract or confuse the viewer.
- Aesthetics: Symmetry often enhances the aesthetic appeal of the visualization, making it visually pleasing and engaging. This can improve user engagement and retention of information.
We hope you’ve been enjoying the Data Design Principles Series.
Keeping design repetition, alignment, and balance in mind will make your visual work stronger and more aesthetically pleasing. These design principles are just guidelines, though. Good designers shouldn’t be afraid to go their own way, following their own instincts.
Now go forth and design!
What should we write about next? Tweet us on Twitter and connect with us on Facebook. We’d love to hear from you!
The Three Principles at a Glance
Each principle earns its place differently, and each has a failure mode worth checking for:
| Principle | What it gives the reader | Common mistake | Quick check |
|---|---|---|---|
| Repetition | One visual language across a report — learn it once, read everything faster | New colours and chart forms on every page | Do the same things look the same everywhere? |
| Alignment | Elements that line up read as related | Decorative centring that breaks the grid | Can you draw straight lines through the layout’s edges? |
| Symmetry | Layouts that feel calm and deliberate | Forcing balance onto lopsided data | Does the layout’s balance match the data’s balance? |
Questions & Answers
What is data visualisation, simply put?
Turning numbers into something the eye can compare. The value is in the comparison — a chart earns its place when seeing two things side by side is faster than reading them.
What does repetition do in a data design?
It makes a set of charts read as one document. Reusing the same colours, spacing and chart forms across a report means a reader learns the visual language once, then spends their attention on the findings.
Why does alignment matter so much in a chart?
Because the eye reads misalignment as meaning. Elements that line up feel related and elements that do not feel separate, so sloppy alignment quietly tells the reader something untrue about the data.
Where does symmetry help, and where does it hurt?
Symmetry gives a layout calm and makes it feel deliberate. It hurts when it is imposed on data that is genuinely lopsided, because a balanced layout implies a balanced story.
Does The Datalabs Agency teach these principles?
Yes. The Datalabs Agency is a Melbourne-based data visualization consultancy founded in 2012 that delivers corporate training workshops (Power BI, Tableau, data storytelling), dashboard design, and BI style guides for clients including Mercedes-Benz, Adidas, and UPS. They are the backbone of the training workshops, and they are what a BI style guide encodes so a team applies them without thinking.
