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Application Data Visualisation Power BI Technology

Create Field Parameters in Power BI

Why is Power BI taking over the world? Why are so many organisations currently implementing Power BI? Power BI is the most efficient tool to manage business intelligence in a world where the data sets are getting bigger and bigger. The importance of making quick and correct decisions is a key factor in running a successful business. Microsoft constantly improves Power BI.  In this blog, we will show you how to create Field Parameters in Power BI.

 

The ‘Creating a Field Parameter’ tool can create a dynamic visual in few seconds, increasing your productivity. This gives the audience interactive options to choose which information they want the visual to display. In the past, we needed to write DAX expressions to achieve this.

In the following example you will see how this is done by creating a table and writing DAX expressions. DAX (Data Analysis epression) is essential to all Power BI reporting and data modelling developers. STL has a one day DAX course for all who need to write DAX in Power BI desktop.

Field Parameters done with DAX

Firstly, you need to create a table. Click Enter Data from the Home tab. In the first column, enter the names of the measures you want to be able to select from a slicer. The slicer will change the visual. Add a second column to create an index (see image below). Name the table at the bottom of this dialog box.

Create Field Parameters in Power BI

Create a Slicer visual and add the Measure column from the created table to the field (see image below).

Create Field Parameters in Power BI

Now it is time to run the DAX measure. You can use the logical Switch function to return the measure selected from the slicer.

Create Field Parameters in Power BI

The logic in the DAX measure is in the image below. The Switch function will test the value selected from the slicer. If the index value is 1 (Sales), it returns the Sales measure, if the index value is 2 (Profit) it returns the Profit measure. Index value 3 (Sales Cost) returns the Sales Cost measure.

Create Field Parameters in Power BI
Creating a visual to show the selected measure from the slicer

The visual (a line chart here) header will not show the selected measure from the slicer, but you can create one by writing another DAX measure.

Visual Name=SelectedValue(slicer1[measure],”Sales”)

This measure will get the selected value (measure name) from the slicer. If nothing is selected from the slicer, it will return the alternate result ‘Sales’ by default.

Now you can use the measure to create a dynamic title for the visual. With the visual selected, you will find the title under the formatting options. Next to the title there is an fx button. When you press the fx button, you can use the measure to create a dynamic title.

Create Field Parameters in Power BI

 

Clicking fx will open the dialog box where you can select the measure which creates the dynamic visual header.

Create Field Parameters in Power BI

The visual will now display the selected value from the slicer as a title!

Create Field Parameters in Power BI

Now to do something similar with the new tool – Creating a field parameter

The new tool we got in the May version of Power BI is a preview feature but will soon be a permanent tool.

Firstly, you will have to enable the tool called Field parameters:

Create Field Parameters in Power BI

Then, to create a new field parameter, you will need to navigate to Modeling > New parameter > Fields

Create Field Parameters in Power BI

To build the parameter, you need to provide a name for the parameter and select the fields you want to use. You can select different dimensions (fields from different tables across your data model) or different measures. The example below starts with different dimensions.

Create Field Parameters in Power BI

From a slicer, select the fields you would like to filter on the visual. If you keep the tick in the bottom left corner, you will create a slicer with the dimensions.

The Field parameters feature will write DAX code to make the slicer and the data model understand what you want.

The DAX code for this example

Filter by dimensions = {

(“ClientName”, NAMEOF(‘tblClients'[ClientName]), 0),

(“Category”, NAMEOF(‘tblProducts'[Category]), 1),

(“SalesRep”, NAMEOF(‘tblSalesRep'[SalesRep]), 2)

}

The slicer will display the field names from your data model. If you want more user-friendly names from the slicer, you can amend the code.

Filter by dimensions = {

(“Client”, NAMEOF(‘tblClients'[ClientName]), 0),

(“Product Category”, NAMEOF(‘tblProducts'[Category]), 1),

(“Sales Rep”, NAMEOF(‘tblSalesRep'[SalesRep]), 2)

}

Adding or removing fields after creating the Field Parameters slicer

Filter by dimensions = {

(“Sales Rep”, NAMEOF(‘tblSalesRep’[SalesRep]), 0),

(“Product Category”, NAMEOF(‘tblProducts’[Category]), 1),

(“Client”, NAMEOF(‘tblClients’[ClientName]), 2),

(“Month”,NAMEOF(Dates[Month Number]),3)

}

In the example above, the Month Number field has been added by amending the DAX code. The slicer will now give the report’s audience the option to break down the visual by month.

Create Field Parameters in Power BI

Using the Field Parameter tool to break down visuals by measures

You can mix and match different measures and dimensions within the same parameter. For example, you can use this feature to create a dynamic table where the columns can be either measures or dimensions.

As shown below, when you use the new Field Parameter feature, the title of the visual will display the selected fields from the slicer. Again, you will not have to write a DAX measure to do this. It can be this easy to create Field Parameters in Power BI.

Create Field Parameters in Power BI

Using a field parameter to control visual properties

Once you have created the field parameters, you can use them to control the measures or dimensions used in a visual.

You can use the parameter in the field drop zones for a visual.

Create Field Parameters in Power BI

Conclusion

The new Field Parameter feature is an efficient way of creating very dynamic visuals. It reduces the number of pages needed for the report to give the audience proper business intelligence. This is, then, how to create Field Parameters in Power BI for your reports.

For more information, please see STL’s two-day Power BI Modelling, Visualisation and Publishing course.

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Data Visualisation Microsoft Office Power BI Technology

How to Efficiently Cleanse and Reshape Data in Power BI

You can improve efficiency and accuracy when pulling and transforming data from various sources by using the Query Editor Tool in Power BI. It’s a marked improvement on using macros in Excel for this function. Read on to see why.

Why use the Query Editor

The Query Editor is where data sourced from a variety of locations can be transformed before loading data into Power BI Desktop to create visuals. It works by making a connection back to the original data source so that whenever changes are made, they are saves as ‘Applied Steps.’ Importantly, they are stored in memory. Meaning that if source data is periodically changed or added to, then a simple refresh in Power BI desktop is all that is needed to update any report visuals based on that data. The process of cleansing and reshaping data can include:

      • replacing values and errors
      • removing duplicates
      • applying Trim to remove unwanted spaces
      • merging and appending data
      • adding/removing columns
      • unpivoting columns

One of the most common problems with analysing data is when the column structure is too rigid – see below:

If you needed to produce reports on each city’s first 6 month’s sales, this would be tricky to accomplish given the current structure. However, there is a solution by using ‘Unpivot Columns’ in Query Editor which effectively restructures the table to produce ‘Month’ and ‘Sales’ columns in addition to the ‘City’ column.

How to use Query Editor

      1. In Power BI Desktop, connect to the source data: GET DATA > EXCEL WORKBOOK
      2. Browse to the Excel Workbook and select the data table in the Navigator dialog box
      3. Click on the ‘Transform Data’ button (bottom right) to launch Query Editor

      1. Note the ‘Applied Step’ section on the right that will expand to include further steps
      2. Now select all the Month Columns, right click on the selection and select ‘Unpivot Columns’ from the list
      3. Rename the ‘Attribute’ column ‘Month (see below)

 

Notice the new structure and also the additional ‘Applied Steps’. To complete the process, apply the changes back to Power BI desktop:

      1. In the Home tab, select ‘Close & Apply’
      2. Create a Column Chart showing Value (sales) against Month
      3. Check in the Data view to see the updated data and new column structure
      4. Now add September’s sales in the Excel table. Save and close the file
      5. Finally in Power BI desktop, select REFRESH in the Home tab and check the chart and data have both updated

Conclusion

The Query Editor is a powerful and extremely useful tool allowing you to repeat routine cleansing tasks on your datasets without the need to do it all manually. This tool will therefore help you become more efficient in the way you manage data. In doing so, you will ultimately increase your productivity.

Further Reading

To find out more about Power BI and when to use Power BI vs. Excel, feel free to have a peruse of the following conversation with one of our trainers: https://www.stl-training.co.uk/b/excel-or-power-bi-which-is-better-for-business-reporting/