Home Business Intelligence Six key rules of knowledge structure

Six key rules of knowledge structure

Six key rules of knowledge structure


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

Data structure is a vital component in designing an excellent dashboard. A well-designed dashboard has a transparent and intuitive means of organizing and presenting information, making it simple in your customers to seek out what they’re in search of.

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

Do you keep in mind enjoying with LEGO bricks? You may put them collectively in limitless methods to construct a lovely dinosaur or a smooth spaceship. But when you do not know your bricks effectively 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 must be intuitive and logical, making it simple for customers to seek 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 usually follows logical or enterprise areas however may also be outlined by particular person wants or firm processes.
  • Navigation: Customers ought to be capable to transfer between completely different dashboards or completely different dashboard sections with ease. This consists of international navigation parts 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: Comparable data must be proven collectively, permitting customers to match and distinction completely different metrics and developments rapidly. Group the knowledge onto separate dashboards or focus them into sections on a single dashboard.
  • Labeling: Labels must be clear, concise, and preserve consistency between particular person charts and dashboards, making it simple for customers to grasp what every metric or development represents.
  • Filtering: Dashboards ought to enable customers to filter out the displayed data in order that they will give attention to probably the most related data.


Dividing data between completely different dashboards permits customers to give attention to a particular set of knowledge or metrics and helps keep away from overwhelming the customers by dumping the entire data on them directly. A very good construction permits customers to understand the out there 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.

Keep in mind that following a logical data construction won’t be sufficient in some instances. The construction has to fulfill the wants and objectives of the particular person. By fastidiously contemplating how data is split and offered, you may create dashboards which are targeted, related, and straightforward to make use of.

Let’s take a look at fashionable assist heart analytics for example. As of late, assist facilities settle for calls, emails, and messages by means of numerous channels. Placing all these metrics collectively may very well be fairly overwhelming, and a few of them are laborious to match on the identical scale; A cellphone 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 cellphone 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 assist channels like cellphone calls or emails.

The proper structure of dashboards allows users to understand both the width and the depth of information.
The right 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 several types of navigation that you would be able to work with on a dashboard:

  • World 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 information factors in additional element, in a distinct view, or in a distinct context. For instance, a person may begin by taking a look at gross sales information for a selected area after which drill right down to see gross sales information 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 is not only about international navigation but additionally native menus, switches, and primarily several types 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 an important data and discover extra particulars as wanted.

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

A visible hierarchy is the association of parts on a dashboard that guides the person’s consideration by means of an important parts on the web page. It’s decided by the dimensions, coloration, 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 towards one another, the dashboard turns into cluttered and laborious to grasp as a result of the group of the knowledge (the logical hierarchy) just isn’t 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 offered data.


Grouping refers back to the means comparable data is organized collectively on a dashboard. It’s used to assist customers rapidly and simply evaluate and acquire insights from completely different metrics and developments proven collectively.

For instance, a monetary dashboard with a number of distinct sections for exhibiting 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 means to make use of grouping on a dashboard is to group completely different metrics or developments by class. For instance, a buyer’s dashboard with a bunch of metrics that’s repeated for each buyer section, similar to first-time prospects, energetic prospects, or high-value prospects. This enables customers to simply evaluate metrics between the shopper segments, and determine developments and patterns.

Let’s take a look at the grouping by class for example of a buyer’s dashboard under. 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 match, for instance, completely different buyer segments.


You may have the best dashboard on the planet, however with out clear labels, it is only a pile of charts with none which means. Labeling is a vital 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 in search of, and they can rapidly parse by means of the completely different sections of the dashboard.

One other necessary good thing about right labeling on dashboards is that it helps to make the info extra visually interesting. Through the use of clear, concise, and constant labels, customers can simply scan the dashboard and rapidly perceive the knowledge being offered. 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 several types of labels a easy column chart might have.


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

Filters enable customers to refine the info displayed on the dashboard in order that they will 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 need 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 right down to any degree of element at the moment mandatory.

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 section.

Wrapping Issues Up

The data structure of a dashboard is a important component of its design. Effectively-designed data structure must be intuitive and logical, permitting customers to roam round freely and making it simple for them to seek out and perceive the knowledge they want. If accomplished appropriately, the utilization of the dashboards turns into so pure that the knowledge structure is sort of invisible. By maintaining the aforementioned rules in thoughts, you may create efficient and fascinating dashboards that assist customers make well-informed selections.

Wish 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 take a look at making use of them your self?



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