When completing financial reporting analysis in Power BI, it is highly likely that you will need to integrate data from many different tables into a format or data structure that works well within the Power BI data model setup. Getting your data model right is essential. To get your data model right for financial reporting
Forecasting analysis in Power BI can be completed in quite an effective manner if you utilise the time intelligence functions in DAX effectively. In this example I wanted to run through the many options you have available to start automatically creating forecasts based on historical information. Your forecasts in a lot of cases will be
Here I dive into the AVERAGEX function. By learning and understanding how to use this function, you very quickly open up a range of analysis that can be incredibly insightful and valuable. Maybe you want to work out the average sales you make per day, per month, per customer, per day, and so on. There
If you want to analyse anything over time, there is likely no more important table to create for any Power BI model that a great date table. I rarely, if ever, run any time analysis over date tables in fact tables. I always create a date table and then build a relationship over to the fact
I want to show you how you can use filter fields and visual interactions in Power BI to great effect. They create simple and very effective ways to make your visualisations easier and more intuitive for the consumer. Filter fields enable you to adjust the results you are showcasing, but instead of having to manually
