Six key rules of knowledge structure


Designing a dashboard that customers will love? Observe these 6 key rules of knowledge structure to make knowledge navigation a breeze.

Data structure is an important factor in designing an excellent dashboard. A well-designed dashboard has a transparent and intuitive method of organizing and presenting knowledge, making it simple in your customers to search out what they’re searching for.

Within the earlier article, I talked about selecting the right chart varieties in your knowledge — in regards to the particular person items you employ for constructing a dashboard. On this article, I’ll inform you the best way to put these items collectively.

Do you bear in mind enjoying with LEGO bricks? You may put them collectively in limitless methods to construct an exquisite dinosaur or a glossy spaceship. But when you do not know your bricks nicely and do not know the way they match collectively, an unpleasant abomination is born. And the identical precept applies when constructing dashboards out of charts.

Data Structure

Data structure ought to be intuitive and logical, making it simple for customers to search out the knowledge they want. It’s pushed by a number of key rules:

  • Construction: How the knowledge is distributed amongst separate dashboards. The construction sometimes follows logical or enterprise areas however may also be outlined by particular person wants or firm processes.
  • Navigation: Customers ought to be capable of transfer between completely different dashboards or completely different dashboard sections with ease. This consists of international navigation elements like menus and native or contextual navigation parts like tooltips, hyperlinks, and drills.
  • Hierarchy: Visible and logical hierarchies should work collectively to create an efficient and user-friendly design.
  • Grouping: Related info ought to be proven collectively, permitting customers to check and distinction completely different metrics and traits rapidly. Group the knowledge onto separate dashboards or focus them into sections on a single dashboard.
  • Labeling: Labels ought to be clear, concise, and preserve consistency between particular person charts and dashboards, making it simple for customers to grasp what every metric or pattern represents.
  • Filtering: Dashboards ought to enable customers to filter out the displayed info in order that they’ll give attention to probably the most related info.


Dividing info between completely different dashboards permits customers to give attention to a particular set of information or metrics and helps keep away from overwhelming the customers by dumping the entire info on them directly. A very good construction permits customers to understand the obtainable breadth of the knowledge first, after which it permits customers to give attention to the realm of curiosity and get into the depth of the knowledge.

Do not forget that following a logical info construction won’t be sufficient in some circumstances. The construction has to satisfy the wants and targets of the particular person. By rigorously contemplating how info is split and introduced, you’ll be able to create dashboards which can be targeted, related, and straightforward to make use of.

Let’s have a look at fashionable help heart analytics for instance. Today, help facilities settle for calls, emails, and messages by way of numerous channels. Placing all these metrics collectively may very well be fairly overwhelming, and a few of them are onerous to check on the identical scale; A telephone name may very well be resolved in seconds or minutes, however an e-mail dialog can final for hours or days. Or the ready time, which is a crucial metric for telephone calls, and the sentiment of the message for emails.

This drawback may very well be solved with an outline dashboard for frequent metrics just like the variety of created or resolved tickets or buyer satisfaction, with the power to drill into separate dashboards for particular help channels like telephone calls or emails.

The proper structure of dashboards allows users to understand both the width and the depth of information.
The correct construction of dashboards permits customers to grasp each the width and the depth of knowledge.

Navigation is a crucial facet of knowledge structure, because it permits customers to effectively transfer across the dashboard and entry the knowledge they want. There are a number of various kinds of navigation which you could work with on a dashboard:

  • International navigation consists of navigation parts that enable customers to maneuver between completely different dashboards or their tabs, for instance, an inventory of dashboards.
  • Native or contextual navigation refers back to the smaller interactive parts throughout the dashboard. Examples of those embody tooltips, hyperlinks, or switches permitting the change of the metric within the chart.
  • Drills are a dashboard-specific sort of interplay that enables customers to discover chosen knowledge factors in additional element, in a special view, or in a special context. For instance, a person would possibly begin by gross sales knowledge for a selected area after which drill all the way down to see gross sales knowledge for particular person cities inside that area.
Navigation on dashboards is not just about global navigation but also local menus, switches, and primarily different types of drills.
Navigation on dashboards isn’t just about international navigation but additionally native menus, switches, and primarily various kinds of drills.


Hierarchy refers to how the knowledge is organized in a logical and visible method in relation to one another. A very good hierarchy permits customers to rapidly and simply determine a very powerful info and discover extra particulars as wanted.

A logical hierarchy refers back to the group and association of knowledge based mostly on its significance or significance. It’s decided by the relationships and connections between completely different items of knowledge — you’ll be able to think about it as a tree-like construction. For instance, a dashboard may need a top-level overview that exhibits key metrics and traits, with the power to discover extra detailed info for every metric.

A visible hierarchy is the association of parts on a dashboard that guides the person’s consideration by way of a very powerful parts on the web page. It’s decided by the scale, shade, place, and different visible traits of the weather.

Visible and logical hierarchies should work collectively to create an efficient and user-friendly design. In the event that they work in opposition to one another, the dashboard turns into cluttered and onerous to grasp as a result of the group of the knowledge (the logical hierarchy) shouldn’t be aligned with how the person’s consideration is drawn to completely different parts on the web page (the visible hierarchy).

The visual hierarchy guides the user's attention, while the logical hierarchy helps them understand the presented information.
The visible hierarchy guides the person’s consideration, whereas the logical hierarchy helps them perceive the introduced info.


Grouping refers back to the method comparable info is organized collectively on a dashboard. It’s used to assist customers rapidly and simply evaluate and achieve insights from completely different metrics and traits proven collectively.

For instance, a monetary dashboard with a number of distinct sections for displaying all income metrics collectively, all expense metrics collectively, and all revenue metrics collectively. This enables customers to get numerous insights about the entire space.

One other frequent method to make use of grouping on a dashboard is to group completely different metrics or traits by class. For instance, a buyer’s dashboard with a gaggle of metrics that’s repeated for each buyer phase, similar to first-time prospects, lively prospects, or high-value prospects. This enables customers to simply evaluate metrics between the shopper segments, and determine traits and patterns.

Let’s have a look at the grouping by class for instance of a buyer’s dashboard beneath. All segments share the identical metrics and visualizations, that are repeated for straightforward comparability between the teams.

Grouping of metrics allows users to compare, for example, different customer segments.
Grouping of metrics permits customers to check, for instance, completely different buyer segments.


You may have the best dashboard on this planet, however with out clear labels, it is only a pile of charts with none that means. Labeling is an important facet of dashboard design, because it helps customers to grasp and interpret the info displayed and supply the context. With clear labels, customers can simply discover the knowledge they’re searching for, and they can rapidly parse by way of the completely different sections of the dashboard.

One other vital good thing about appropriate labeling on dashboards is that it helps to make the info extra visually interesting. By utilizing clear, concise, and constant labels, customers can simply scan the dashboard and rapidly perceive the knowledge being introduced. When interested by labels, keep away from abbreviations and technical phrases, as they are often complicated for customers.

The different types of labels a simple column chart may have.
The various kinds of labels a easy column chart could have.


It is nice to have a chicken’s-eye view of your knowledge, however usually it is essential to have the ability to dig into the main points and work out what’s mistaken. That is the place filtering turns out to be useful. On the planet of dashboard design, filtering is sort of a treasure map, narrowing down the realm during which to dig for insights.

Filters enable customers to refine the info displayed on the dashboard in order that they’ll focus simply on the precise piece of knowledge that’s most related to them.

A standard method to filtering is to make use of drop-down menus that enable customers to decide on particular standards for the info they wish to see. One other method is to make use of interactive parts, similar to buttons or sliders, that allow customers to dynamically change the info displayed. The next instance exhibits a company-wide overview dashboard which may be filtered all the way down to any degree of element at present crucial.

Filtering can change a company-wide dashboard into a hyper-focused view of a single country, business unit, product category, and customer segment.
Filtering can change a company-wide dashboard right into a hyper-focused view of a single nation, enterprise unit, product class, and buyer phase.

Wrapping Issues Up

The data structure of a dashboard is a important factor of its design. Properly-designed info structure ought to be intuitive and logical, permitting customers to roam round freely and making it simple for them to search out and perceive the knowledge they want. If completed accurately, the utilization of the dashboards turns into so pure that the knowledge structure is nearly invisible. By holding the aforementioned rules in thoughts, you’ll be able to create efficient and interesting dashboards that assist customers make well-informed selections.

Need to it strive for your self?

If you wish to put any of those rules to work, why not register for the free GoodData trial and check out making use of them your self?


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