Introduction to Report Design for Filtering - Training

Introduction to Report Design for Filtering - Training

In Microsoft Power BI, filtering can occur at five different levels: semantic model (RLS), report page, visual, and measure. The report level, page level, and visual level filters are applied to the structure of the report. Each Power BI report queries a unique semantic model, which is a Power BI artifact that represents a semantic model. A report cannot determine if the semantic model will apply RLS and cannot override RLS. The structure of a Power BI report is hierarchical. A measure is a model object designed to summarize data and can modify the filter context using the CALCULATE or CALCULATETABLE functions. Time intelligence functions also modify the filter context. During report design in Microsoft Power BI Desktop, you can create measures.

Selection of Report Visual Objects - Training

Tables and matrices can effectively convey a large amount of detailed information. You can take a line chart to the next level by adding an analysis option. You should avoid a line chart with a categorical X-axis because the line implies a relationship between elements that may not exist. Choosing the wrong type of visual object could make it difficult for report consumers to understand the data or, worse, could lead to a misrepresentation of the data. Bar or column charts are good choices when you need to display data in multiple categories. In most cases, you should sort category charts by value rather than alphabetically by category. If values may be missing, a column chart may be a better visual object option as it will help avoid interpreting a non-existent trend. Ribbon chart, stacked column chart, area chart, and stacked column and line chart have the additional advantage of showing ranking changes over time. Column and bar chart visual objects work well for visualizing proportions across multiple dimensions. Proportional visual objects cannot plot a combination of positive and negative values. They should be used when all values are positive or all values are negative. 100% stacked column chart for proportional visualization. Funnel chart, treemap chart, sunburst chart, and pie chart for categorical visualization. Matrix provides one of the best experiences for hierarchical navigation. It allows users to explore in-depth, in columns or rows, to detect detailed data points of interest. When applying conditional formatting, data bars help report consumers quickly understand the distribution of values and display KPI performance. Table with conditional formatting and matrix with conditional formatting. When a semantic model has geospatial information, it can be conveyed using map visual objects. The choropleth map visual object of the United States may not sufficiently convey sales by city. If you elevate the granularity to the state level, the choropleth map visual object will generate a better result than the map visual object. A map visual object can take up considerable space on the report page. Additionally, geospatial data doesn't always have to be shown on maps. If location is not highly relevant to the requirements, consider using a categorical visual object instead.

In conclusion, designing reports in Microsoft Power BI requires understanding the different levels of filtering and selecting appropriate visual objects. By considering the type of data and the goals of the report, you can effectively communicate information to report consumers. Here are three actionable tips to improve report design:

1. Consider the granularity of your data: Depending on the level of detail required, choose visual objects that can effectively convey the information. Avoid using visual objects that imply relationships that may not exist.

2. Use conditional formatting: Applying conditional formatting, such as data bars, can help report consumers quickly understand the distribution of values and identify performance trends. This can enhance the visual appeal and usability of the report.

3. Choose the right visual object for geospatial data: When working with geospatial data, consider the level of granularity needed and choose visual objects that can effectively convey the information. Maps are not always the best option, especially if location is not highly relevant to the report requirements. Consider using categorical visual objects instead.

By following these tips, you can create visually appealing and informative reports in Microsoft Power BI. Remember to consider the specific needs of your audience and adapt your design choices accordingly.