As an HR, marketing or operational team member, you may have been confronted with situations where you need to set up individual Teams sessions for a series of colleagues.
Wouldn’t it be nice if you could just create and describe those sessions in an Excel table and use that table to create all sessions automatically in Teams at the push of a button?
Well… you can! Power Automate makes it easy to set up automations like this one.
In most organisations, reports in Power BI and on other BI platforms are created by specialists in consultation with the person who requested the report. While these reports meet most expectations, there are situations where users need or want to have their data presented in a different way. They might want to include an additional perspective that wasn’t in the original report, for example.
This need is often temporary and doesn’t require the existing report to be changed.
To accommodate this, Power BI now offers users the option to change the way visuals are displayed. This option is called ‘Personalize Visuals’. The precursor to this option, ‘Decomposition Tree’, was similar in some ways. In this blog post, I’ll shed some light on both options.
When you create a report in Power BI, you can use different kinds of visuals which are designed to let you analyse data from different perspectives. There are also several methods available to distil additional information from your data, such as drill-down, drill-through, and interactivity between visualisations.
In many organisations, Power BI reports or data sets are created centrally. For reports, this means the organisation aims to create them with a standard setup.
Power BI is a ‘Self-Service BI’ platform, a solution that was developed to give any average user the means to build their own reports and gain insight into specific analyses or questions. Of course, Power BI offers a ‘light’ version of BI, because not everyone is knowledgeable about BI or has experience with it.
One of the things you can do with Power BI is create reports based on existing data sets. Data sets are the foundation of a report: they contain one or several data sources that have been prepared for use in a data set where needed, as well as the necessary calculations for the analyses performed on these data.
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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