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Control the visibility of the PowerBI visuals based on condition

In PowerBI, there is no direct or functional mechanism to adjust the visibility (Show/Hide) of visualizations based on filter choices. There is, however, a workaround that enables us to show/hide visuals based on filter condition.

The fundamental concept behind this technique is to apply a mask to a visual and change its opacity based on a condition or filter selection.

Use Case:

I have detail table of orders. These orders are divided into Consumer, Home Office, and Corporation categories. I use segment as a filter. One of the requirements is to present a table of detail if the overall profit for the selected segment is less than $100,000. To do this, this task will be divided into two major parts. First, we will display the table if the filter is selected. Next, we will add a condition to the table.

Step 1: Show table only filter is selected

  • Place filter (Slicer) and visual on the Report Pane.

  • Create a measure that will determine if the filter is selected or not.

Filter_Selected = IF(ISFILTERED(Orders[Segment]),1,0)

  • Add this measure to the filter pane of the table visualization and select the show item when the value is 1 option. This will ensure that when no options are selected, only the header is displayed.

  • Set the mask down on the table. Make sure you only mask the table header with a border color that matches your background, or remove it entirely.

  • Create a measure to change the mask’s transparency. If two zeros are appended to the end of any HAX code, this represents complete transparency.

mask_transparency =IF([Filter_Selected],”#FFFFFF00″,”#FFFFFF”)

  • Keep this measure on the Fill of the mask and add conditional formatting to it.

If the mask transparency(measure) field is grayed out during the previous steps, you may need to modify the data type of mask transparency to text.

Step 2 : Add a condition to the solution

  • Create a new measure to determine if our condition is met.

condition_check = IF(CALCULATE(SUM(Orders[Profit]),filter(all(Orders), Orders[Segment] = SELECTEDVALUE(Orders[Segment]))) < 100000,1,0)

  • Now add this new measure to a table visual’s filter pane and pick the show item when the value is 1 option. This ensures that only if the condition meets the table will appear.

You can now display or hide visuals based on slicer selection and condition. If you know a better way to do this, please comment and let me know. For this article, I referred to this page.

 

process.science presents a new release

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Process Mining Tool provider process.science presents a new release

process.science, specialist in the development of process mining plugins for BI systems, presents its upgraded version of their product ps4pbi. Process.science has added the following improvements to their plug-in for Microsoft Power BI. Identcal upgrades will soon also be released for ps4qlk, the corresponding plug-in for Qlik Sense:

  • 3x faster performance: By improvement of the graph library the graph built got approx. 300% more performant. This is particularly noticeable in complex processes
  • Navigator window: For a better overview in complex graphs, an overview window has been added, in which the entire graph and the respective position of the viewed area within the overall process is displayed
  • Activities legend: This allows activities to be assigned to specific categories and highlighted in different colors, for example in which source system an activity was carried out
  • Activity drill-through: This makes it possible to take filters that have been set for selected activities into other dashboards
  • Value Color Scale: Activity values ​​can be color-coded and assigned to freely selectable groupings, which makes the overview easier at first sight
process.science Process Mining on Power BI

process.science Process Mining on Power BI

Process mining is a business data analysis technique. The software used for this extracts the data that is already available in the source systems and visualizes them in a process graph. The aim is to ensure continuous monitoring in real time in order to identify optimization measures for processes, to simulate them and to continuously evaluate them after implementation.

The process mining tools from process.science are integrated directly into Microsoft Power BI and Qlik Sense. A corresponding plug-in for Tableau is already in development. So it is not a complicated isolated solution requires a new set up in addition to existing systems. With process.science the existing know-how on the BI system already implemented and the existing infrastructure framework can be adapted.

The integration of process.science in the BI systems has no influence on day-to-day business and bears absolutely no risk of system failures, as process.science does not intervene in the the source system or any other program but extends the respective business intelligence tool by the process perspective including various functionalities.

Contact person for inquiries:

process.science GmbH & Co. KG
Gordon Arnemann
Tel .: + 49 (231) 5869 2868
Email: ga@process.science
https://de.process.science/

Business Intelligence – 5 Tips for better Reporting & Visualization

Data and BI Analysts often concentrate on learning a BI Tool, but the main thing to do is learn how to create good data visualization!

BI reporting has become an indispensable part of any company. In Business Intelligence, companies sometimes have to choose between tools such as PowerBI, QlikSense, Tableau, MikroStrategy, Looker or DataStudio (and others). Even if each of these tools has its own strengths and weaknesses, good reporting depends less on the respective tool but much more on the analyst and his skills in structured and appropriate visualization and text design.

Based on our experience at DATANOMIQ and the book “Storytelling with data” (see footnote in the pdf), we have created an infographic that conveys five tips for better design of BI reports – with self-reflective clarification.

Direct link to the PDF: https://data-science-blog.com/en/wp-content/uploads/sites/4/2021/11/Infographic_Data_Visualization_Infographic_DATANOMIQ.pdf

About DATANOMIQ

DATANOMIQ is a platform-independent consulting- and service-partner for Business Intelligence and Data Science. We are opening up multiple possibilities for the first time in all areas of the value chain through Big Data and Artificial Intelligence. We rely on the best minds and the most comprehensive method and technology portfolio for the use of data for business optimization.

Contact

DATANOMIQ GmbH
Franklinstr. 11
D-10587 Berlin
I: www.datanomiq.de
E: info@datanomiq.de