Como crear un Velocímetro (Gauge Visual) | Capítulo 10 | Curso de Power BI

How to Create a Speedometer Chart in Power BI

Introduction to Speedometer Charts

• Speedometer charts are visually appealing and easy for many users to understand, but creating one in Excel can be challenging. This tutorial will guide you through the steps of creating a speedometer chart in Power BI.

• Power BI offers a built-in visualization called "gauge," commonly known as speedometers or tachometers, making it easier to create these charts without needing external downloads.

Setting Up the Data

• An example project has been prepared with sales data by year, which will serve as a reference for constructing the speedometer chart.

• The average annual sales from 2014 to 2017 is calculated at approximately 353 million, which will be used as a benchmark for comparison against yearly sales.

Creating the Gauge Chart

• To start building the gauge chart, click on the gauge icon; this inserts a blank box below the visualization panel where data input is required (value field, minimum value, maximum value, target value).

• It’s important that databases analyzed in Power BI are accurate and well-structured. However, alternative options exist if direct configuration isn’t possible due to database limitations.

Configuring Values for Visualization

• Dragging the "total revenue" field into the values area shows over 1.4 billion in total income. A filter for year is added at this stage.

• After applying filters for specific years (e.g., selecting only 2014), we see that revenues amount to 438 million for that year.

Manual Adjustments and Formatting

• Since direct configuration of minimum and maximum values isn't feasible with our dataset, manual entry is necessary: set minimum at 0 and maximum at 500 million.

• The target value is set at 353 million (the average). Adjustments are made to enhance visibility by changing colors and sizes of labels.

Interpreting Results

• The resulting gauge indicates that revenues from 2014 were significantly above average (438 million vs. target of 353 million), clearly shown through color coding.

Replicating Visualizations for Other Years

• For subsequent years like 2015, Power BI allows copying existing visualizations while adjusting minimal elements—saving time during setup.

Building from Scratch: Yearly Analysis

• When creating a new gauge from scratch for another year (e.g., 2016), repeat previous steps: drag fields into place and apply relevant filters.

Finalizing Comparisons Across Years

Analysis of Business Performance in 2017

Overview of 2017 Financial Results

• The year 2017 was identified as the worst for the business, with revenues at only 268 million, marking a significant decline compared to previous years.

• There was a notable loss of nearly 90 million relative to the average determined initially, indicating poor financial health during this period.

Dashboard and Performance Metrics

• A dashboard featuring four simple speedometers was constructed to visualize performance metrics effectively; these are designed for easy understanding without requiring advanced skills.

• Each speedometer fills based on results, providing an immediate visual reference to assess whether good outcomes have been achieved.