Share this
September 8th
February 22ndVisualizing and comparing data that shows trends over time is one of the essential things you must get right when solving certain business questions. Especially when you deal with forecasts or seasonal analysis.
But when it comes to working with time periods in Power BI, you can’t do it without knowing your way around DAX functions and Power Query.
To eliminate any seasonality or fluctuations, it’s imperative to show your performance compared to a rolling or a moving average. What about visualizing your sales performance for the current month that refreshes automatically?
Join this webinar to learn how to implement it immediately.
Functionally, it's completely the same. It's easier just to have the date and create a relationship with your dates. In reality, if you have a small model and you load the data, it does not make a huge difference. Where it does matter, is if you're working with a huge data model with millions of rows. In this case, you will make one step toward the performance optimization because the date ID is shorter.
The date-time relationships between the fact and dimension tables don't have the best compression, so that's the reason we need integers.
Yes, absolutely. Most of the things that we showed here will work with any custom and native Power BI visuals.
Yes, it is possible. You need to make sure that the relationship that you will build between your fact table and the dimension, uses the same field. It's probably the easiest to build the Date ID field and build a relationship to your Power BI calendar table. The purpose of the calendar table is in fact to leverage all the time intelligence functions.
