Most Power BI users are impressed with the possibility to create custom visuals, which sometimes results in very colourful reports/dashboards – and occasionally even leads to documents that teeter on the edge between looking professional or amateurish. Where do you need to draw the line?
Like several similar solutions, Power BI works best if data are structured in a star schema, which is a structure that consists of fact and dimension tables. Typically, one of these dimensions is the date dimension. This dimension can filter your data based on calendar-type fields. If there are multiple Date fields in the fact table (such as OrderDate, DueDate, ShipDate…), there are some considerations to take into account.
As mentioned in earlier posts, Power BI uses an expression language called DAX (Data Analysis Expressions) to create calculations. At first glance, this language is similar to Excel formulas, but there are some important differences. Most importantly, DAX uses a row and filter context when executing expressions.
When you start using DAX, you might think that it looks strangely much like Excel formulas – but while they do look similar, they work in completely different ways. In order to execute calculations correctly, it’s important that you understand these differences.
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