Power BI Knowledge-Base
Table of Contents
Power BI is a data analysis and visualization tool available to all faculty, students, and staff at Ohio University. It can be used to create visualizations and reports using data from a variety of data sources, including local, shared files, and databases (if you have access to them). These reports can then be used to gain insights into your data to help you make decisions.
Power BI uses a model-centric approach to handling data. This means that you can bring in multiple tables and relate them using columns with the same data. Power BI is designed to aggregate data across columns or tables on the fly for visualizations, either by using the columns themselves or through measures for more complicated calculations (see below). You can then either use the columns themselves or measures to create visualizations that allow users to understand data even from highly complex datasets.
Regardless of the project you're planning with Power BI, they usually follow the same generalized steps.
- Loading the data. This can be anything from finding a flat file on your computer to connecting to a database.
- Preparing and cleaning the data. Data often needs to be cleaned and prepared before it can be used. This is done through Power Query.
- Creating visuals and measures with the data. These are often done together as you’re building your report.
There are a few best practices for data analysis:
- Do as much of the cleaning and preparing of your data as you can before bringing the data into Power BI (in excel, this usually means having a flat table, a single row of headers at the top, and all the data in a column are the same data type).
- Any transformations that need to occur after bringing in the data to Power BI should be done in Power Query
Altering data in the Power BI report itself should be done only as a last resort.