Hello fellow developers and data enthusiasts,
I've put together a comprehensive set of 12 Power BI design best practices based on my insights and explorations in the data realm. I'd love to get your thoughts and feedback on these principles!
1.Understand Your Target Audience
Design a dedicated view for each sort of audience.
Example:
Leaders should have an executive view on what they are concerned about, whereas customers should have a low-level perspective on what they are engaging in.
Before designing a view, consider the employee's kind of job; for example, providing a financial balance sheet to a non-financial employee is pointless.
2.Define Clear Objectives
Always begin with an understanding of your dashboard's primary goal and the problem that needs to be solved.
Example:
If you're developing a sales performance dashboard, your goal may be to deliver real-time insights on revenue, sales trends, and product performance to assist sales teams in making data-driven decisions.
3.Choose the Appropriate Visualizations
Choose relevant data visualizations.
Example:
Use a bar chart to demonstrate how different product categories contribute to overall income.
Show the progression of revenue over time with a bar/line chart.
A map visualization may be more successful than a pie chart for showing geographical sales data.
4.Break the problem and solve by visual
Break the problem into numerous questions that address the problem, then construct each visual such that it answers at least one of the questions/doubts presented in the analysis.
Example:
Each visual on the Sales Dashboard should address or resolve each issue or doubt raised through the sales analysis.
5.Design with consistency
Maintain consistency in design, layout, and formatting throughout every component of the dashboard for a consistent user experience.
Example:
Make ensure that all charts and graphs use the same color scheme or pattern of similar data points across several visuals (i.e., Profit – Green color, Loss – Red color) and maintain organizational design standards all over the dashboard.
6.Use Reports/Dashboard in the appropriate place.
Develop reports when an in-depth and comprehensive examination is required, and dashboards when quick overview, executive summaries, and real-time monitoring is required.
Example:
Report:
(Descriptive & Diagnostic Analysis)
In Sales Report, what has happened in the past two years and why it has happened should be addressed.
Dashboard:
(Predictive & Prescriptive Analysis)
In Sales Dashboard, with minimal information about what has happened and prescribing what to do in future to solve this can be addressed.
7.Ensure visibility.
Maintain users informed of ongoing activities, such as data loading or refreshing.
Example:
Using icons or a progress bar to illustrate the state of a data refresh process, as well as indications to identify when they were last updated (to demonstrate how old the data is).
8.Design with freedom.
Allow users to quickly customize data with filters, slicers, and interactive components. Allow users to rollback or undo actions.
Example:
Providing filter choices for date ranges (e.g., particular dates, quarters, or years) to enable different data analysis, giving drill-down charts for exploring data, and allowing users to reverse changes by providing Back navigation and clear slicers options where necessary to undo an operation.
9.Use Meaningful and Contextual Labels.
To provide context and improve understanding, use clear and descriptive labels for charts, graphs, and filters etc.
Example:
Use terms like "Monthly Revenue Trends" or "Sales by Region" rather than "Revenue Data" or "Sales Information" instead of generic labels.
10.Use white space effectively.
Make thoughtful use of white space to improve readability and identify important details.
Example:
To avoid congestion and promote understanding, space out graphics and text sections.
11.Improve user Engagement.
To increase user involvement and study, use interactive components like as filters, slicers, and tooltips.
Example:
Include data slicers that allow users to filter data by date ranges or category of products, allowing for customized analysis.
12.Help the user.
With pop-ups and documents, assist the user in understanding the action they are performing.
Example:
Including help icons with precise documentation, as well as providing tooltips to visualizations that explain the relevance of individual data points or trends.
I believe these practices are crucial for creating impactful and user-friendly reports. However, I'm eager to hear about your journeys. Have you found similar principles effective? Do you have additional tips to enhance Power BI design?
Your feedback is invaluable! Feel free to share your thoughts or suggest any other practices you've discovered during your expeditions in the realm of Power BI. Let's collaborate and further enrich our data voyages together!
