Hi, we are Gizelle Gopez, Michele Sadler, Kim Ho, and Cathy Lesesne from Deloitte’s Evaluation for Research and Action Center of Excellence. As evaluation consultants, we work with federal evaluation clients to transform their data into actionable insights. Several data visualization tools have been effective in producing reports and dashboards for monitoring, data interpretation sessions, and quality improvement efforts resultant from evaluations. Power BI is one such tool able to connect to various data sources, combine data, and visualize it to help tell a story of what is happening in a program or service that is being evaluated. For instance, our work with federal clients has included using Power BI to synthesize and longitudinally follow hundreds of indicators to track the impact of health equity initiatives or track deployment of public health professionals across the nation during the height of the COVID-19 pandemic.
Below are some high-level steps to help you get started using Power BI as part of your evaluation toolbox!
Step 1: It is important to first have a stated purpose and clear evaluation question(s) for the use of your data. Having clear questions will help to focus what you are trying to measure and therefore the type of data needed. Specifying the types of data that will be needed and the format of the data will determine the utility of tools like Power BI for your evaluation.
Step 2: Once you have determined your evaluation purpose and questions and collected your data, the next step is to get your data into the Power BI interface. Power BI will allow you to easily connect to and extract data from a variety of data sources such as Excel, DQL Service, Text/CSV, SharePoint, SQL Database and more.
Step 3: Once data are extracted as tables in the Power BI interface, you will need to transform and clean your data, by filtering, splitting columns, changing data types, and other transformations so that the data are in a form to answer your evaluation questions. Performing these data transformation and cleaning steps in Power BI allows you to store and automatically apply the steps when you refresh your data, saving you time by not having to repeat steps.
Step 4: Next you can build out your data model, connecting multiple data sources together to further answer your evaluation questions. You can do this by adding lookup keys, joining tables, and aggregating the data. Lookups can be used to match data between different tables without having to join or merge them. Joining allows you to combine data from different tables based on a common column. Aggregations can be used to summarize and group data to see any trends or patterns. These functions allow you to combine and manipulate data from different sources to gain additional insights.
Step 5: Once your data are loaded and transformed, you can create different visualizations of your data using any of the 24 different types of visualizations built into Power BI or you can install and use one of the more than 300 additional visualization types available from Microsoft AppSource marketplace.
Learning from the many freely accessed examples as well as trial and error experimentation with the interface will reveal the endless ways you can use the tool for analysis, data linkage, data viz, and communication with partners.
Rad Resources
- Get familiar with the Power BI interface with a free version of the tool: Get Power BI Desktop – Power BI | Microsoft Learn
- Power BI Full Course – Learn Power BI in 4 Hours | Power BI Tutorial for Beginners | Edureka – YouTube
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