Design and Formatting of Pages in Power BI Desktop

Design and Formatting of Pages in Power BI Desktop

Power BI Desktop offers a range of features to control the design and formatting of report pages, allowing users to customize the layout and appearance of their reports. By using the Page View menu on the View tab, users can easily adjust the scale of report pages. The available options include Fit to Page (default), Fit to Width, and Actual Size.

In addition to the default 16:9 page size, Power BI Desktop also includes a 4:3 Dynamic option, which stretches the page to fill the available space. Users can also specify a custom page size by setting the dimensions in inches or pixels. Furthermore, it is possible to change the background color of the entire report, providing further customization options.

Another useful feature is the ability to control the overlapping of elements in a report. When there are multiple elements in a report, Power BI allows users to determine how they are overlapped with each other using the Z-order.

Selection of Visual Objects in Reports

Choosing the right visual object is crucial for effectively conveying information in reports. Tables and matrices are particularly effective for presenting detailed information, as they can accommodate a large amount of data. However, it is important to consider the type of analysis required. For example, a line chart with a categorical X-axis may imply relationships between elements that do not exist, so it is important to avoid this setup.

Bar and column charts are excellent options when presenting data across multiple categories. In most cases, it is advisable to sort the category charts by value rather than alphabetically. This ensures that the charts accurately represent the data and prevent the misinterpretation of trends. Additionally, a column chart may be a better choice when dealing with missing values, as it avoids misrepresenting a non-existent trend.

Other visual objects, such as ribbon charts, stacked column charts, area charts, and combination charts, offer unique benefits for displaying changes in ranking over time. Bar and column charts are effective for visualizing proportions across multiple dimensions. However, it is important to note that proportional visual objects cannot represent a combination of positive and negative values. They should only be used when all values are either positive or negative.

Matrix visual objects provide an excellent user experience for hierarchical navigation. They allow users to explore data in-depth, drilling down into columns or rows to identify detailed data points of interest. By applying conditional formatting, data bars can be used to quickly understand value distribution, while KPI tables and matrices with conditional formatting can effectively display performance indicators.

When a semantic model includes geospatial information, it can be effectively conveyed using map visual objects. However, it is important to consider the level of granularity required. For example, a choropleth map of the United States may not effectively convey sales data by city. In such cases, raising the granularity to the state level can generate better results. Additionally, it is worth noting that map visual objects can occupy a significant amount of space on a report page. If location is not a critical factor, consider using categorical visual objects instead.

Actionable Advice:

1. Consider the type of analysis required when choosing visual objects for your reports. Ensure that the selected objects accurately represent the data and avoid misinterpretation.
2. When dealing with missing values, use visual objects such as column charts that can effectively display data without implying non-existent trends.
3. When presenting geospatial information, carefully consider the level of granularity required and choose the appropriate visual object accordingly.

In conclusion, the design and formatting of pages in Power BI Desktop play a crucial role in effectively conveying information in reports. By utilizing the various options and features available, users can customize the layout, appearance, and overlapping of elements to create visually appealing and informative reports. Additionally, by carefully selecting the appropriate visual objects and considering the analysis requirements, users can ensure that their reports accurately represent the data and facilitate better understanding for consumers.