This article documents how to accomplish a number of use cases using the Customer Journey Analytics BI extension. Each use case explains the Customer Journey Analytics functionality, followed with details for each of the BI tools supported:
Power BI Desktop. The version used is 2.137.1102.0 64-bit (October 2024).
Tableau Desktop. The version used is 2024.1.5 (20241.24.0705.0334) 64-bit.
The connect use case focuses on how to connect BI tools using the Customer Journey Analytics BI extension.
The report and analysis use cases instruct how to accomplish similar Customer Journey Analytics visualizations in the BI tools currently supported.
The understand use cases provide more details on:
Transformations that occur when you use a BI tools to report and analyze.
Visualization similarities and differences between Customer Journey Analytics and BI tools.
Caveats of each of the BI tools you should be aware of.
Connect and validate
This use case sets up the connection from the BI tool to Customer Journey Analytics, lists the available data views, and selects a data view to use.
Customer Journey Analytics
The instructions refer to an example environment with the following objects:
Data view: C&C - Data View π .
Dimensions: Product Name π and Product Category π .
Metrics: Purchase Revenue π and Purchases π .
Filter: Fishing Products π .
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When you go through the use cases, replace these example objects with objects that are appropriate for your specific environment.
BI tools
tabs
Power BI Desktop
Access the required credentials and parameters from the Experience Platform Query Service UI.
Navigate to your Experience Platform sandbox.
Select
Queries from the left rail.
Select Credentials tab in the Queries interface.
Select prod:cja from the Database dropdown menu.
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Start Power BI Desktop.
From the main interface, select Get data from other sources.
In the Get Data dialog:
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Search for and select PostgreSQL database.
Select Connect.
In the PostgreSQL database dialog:
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Use
to copy and paste the Host and Port values from the Experience Platform QueryExpiring Credentials panel, separated by : as the value for Server. For example: examplecompany.platform-query.adobe.io:80.
Use
to copy and paste the Database value from the Experience Platform QueryExpiring Credentials panel. Add ?FLATTEN to the value that you paste. For example, prod:cja?FLATTEN.
Select DirectQuery as the Data connectivity mode.
Select OK.
In the PostgreSQL database - Database dialog:
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Use
to copy the Username and Password values from the Experience Platform QueryExpiring Credentials panel in the User name and Password fields. If you are using a non-expiring credential, use the password of your non-expiring credential.
Ensure that the dropdown menu for Select which level to apply these settings to is set to the Server that you have defined earlier.
Select Connect.
In the Navigator dialog, the data views are retrieved. This retrieval can take some time. Once retrieved, you see the following in Power BI Desktop.
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Select public.cc_data_view from the list in the left panel.
You have two options:
Select Load to continue and finish the setup.
Select Transform Data. You see a dialog where you can optionally apply transformations as part of the configuration.
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Select Close & Apply.
After a while, public.cc_data_view is displayed in the Data pane. Select
to show dimensions and metrics.
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To FLATTEN or not
Power BI Desktop supports the following scenarios for the FLATTEN parameter. See Flatten nested data for more information.
Access the required credentials and parameters from the Experience Platform Query Service UI.
Navigate to your Experience Platform sandbox.
Select
Queries from the left rail.
Select Credentials tab in the Queries interface.
Select prod:cja from the Database dropdown menu.
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Start Tableau.
Select PostgreSQL from the left rail underneath To a Server. If not available, select More⦠and select PostgreSQL from the Installed Connectors.
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In the PostgreSQL dialog, in the General tab:
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Use
to copy and paste the Host from the Experience Platform QueryExpiring Credentials panel to the Server.
Use
to copy and paste the Port from the Experience Platform QueryExpiring Credentials panel to the Port.
Use
to copy and paste the Database from the Experience Platform QueryExpiring Credentials panel to the Database. Add %3FFLATTEN to the value that you paste. For example: prod:cja%3FFLATTEN.
Select Username and Password from the Authentication dropdown menu.
Use
to copy and paste the Username from the Experience Platform QueryExpiring Credentials panel to the Username.
Use
to copy and paste the Password from the Experience Platform QueryExpiring Credentials panel to the Password. If you are using a non-expiring credential, use the password of your non-expiring credential.
Ensure that Require SSL is checked.
Select Sign In.
You see a Progressing Request dialog while Tableau Desktop validates the connection.
In the main window, you see in the Data Source page, in the left pane:
The name of the connection, underneath Connections.
The name of the database, underneath Database.
A list of tables, underneath Table.
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Drag the cc_data_view entry and drop the entry on the main view that reads Drag tables here.
The main window displays details of the cc_data_view data view.
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To FLATTEN or not
Tableau Desktop supports the following scenarios for the FLATTEN parameter. See Flatten nested data for more information.
In this use case, you want to display a table and simple line visualization that shows a daily trend of occurrences (events) from January 1, 2023 up until January 31, 2023.
You see a table displaying the occurrences for the current month. For better visibility, enlarge the visualization.
In the Filters pane:
Select the daterangeday is (All) from Filters on this visual.
Select Advanced filtering as the Filter type.
Define the filter to Show items when the valueis on or after1/1/2023Andis before2/1/2023. You can use the calendar icon to pick and select dates.
Select Apply filter.
You see the table updated with the applied daterangeday filter.
In the Visualizations pane, select the Line chart visualization.
A line chart visualization replaces the table while using the same data as the table. Your Power BI Desktop should look like below.
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On the Line chart visualization:
Select
.
From the context menu, select Show as a table.
The main view is updated to show both a line visualization and a table. Your Power BI Desktop should look like below.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from the Data source view. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates and specify a period of 01/01/2023 - 01/02/2023.
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Drag and drop Daterangeday from the Tables list in the Data pane and drop the entry in the field next to Columns.
Select Day from the Daterangeday dropdown menu, so that the value is updated to DAY(Daterangeday).
Drag and drop Occurrences from the Tables (Measure Names) list in the Data pane and drop the entry in the field next to Rows. The value is automatically converted to SUM(Occurrences).
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select Duplicate from the Sheet 1 tab context menu to create a second sheet.
Select Rename from the Sheet 1 tab context menu to rename the sheet to Graph.
Select Rename from the Sheet 1 (2) tab context menu to rename the sheet to Data.
Ensure that the Data sheet is selected. In the Data view:
Select Show me at the top right and select Text table (upper left top visualization) to modify the content of the Data view to a table.
Select Swap Rows and Columns from the toolbar.
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select the New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Graph sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Data sheet from the Sheets shelf below the Graph sheet onto the Dashboard 1 view.
Select the Data sheet in the view and modify Entire View to Fix Width.
Your Tableau Desktop should look like below.
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Hourly trend
In this use case, you want to display a table and simple line visualization that shows an hourly trend of occurrences(events) for January 1, 2023.
Power BI does not understand how to handle date-time fields, so dimensions like daterangehour and daterangeminute are not supported.
Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates and specify a period of 01/01/2023 - 02/01/2023.
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Drag and drop Daterangehour from the Tables list in the Data pane and drop the entry in the field next to Columns.
Select More > Hours from the Daterangeday dropdown menu, so that the value is updated to HOUR(Daterangeday).
Drag and drop Occurrences from the Tables (Measure Names) list in the Data pane and drop the entry in the field next to Rows. The value is automatically converted to SUM(Occurrences).
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select Duplicate from the Sheet 1 tab context menu to create a second sheet.
Select Rename from the Sheet 1 tab context menu to rename the sheet to Graph.
Select Rename from the Sheet 1 (2) tab context menu to rename the sheet to Data.
Ensure that the Data sheet is selected. In the Data view:
Select Show me at the top right and select Text table (upper left top visualization) to modify the content of the Data view to a table.
Drag HOUR(Daterangeday) from Columns to Rows.
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Graph sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Data sheet from the Sheets shelf below the Graph sheet onto the Dashboard 1 view.
Select the Data sheet in the view and modify Entire View to Fix Width.
Your Dashboard 1 view should look like below.
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Monthly trend
In this use case, you want to display a table and simple line visualization that shows a monthly trend of occurrence (events) for 2023.
You see a table displaying the occurrences for the current month. For better visibility, enlarge the visualization.
In the Filters pane:
Select the daterangemonth is (All) from Filters on this visual.
Select Advanced filtering as the Filter type.
Define the filter to Show items when the valueis on or after1/1/2023Andis before1/1/2024. You can use the calendar icon to pick and select dates.
Select Apply filter.
You see the table updated with the applied daterangemonth filter.
In the Visualizations pane:
Select the Line chart visualization.
A line chart visualization replaces the table while using the same data as the table. Your Power BI Desktop should look like below.
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On the Line chart visualization:
Select
.
From the context menu, select Show as a table.
The main view is updated to show both a line visualization and a table. Your Power BI Desktop should look like below.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates and specify a period of 01/01/2023 - 01/01/2024.
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Drag and drop Daterangeday from the Tables list in the Data pane and drop the entry in the field next to Columns.
Select MONTH from the Daterangeday dropdown menu, so that the value is updated to MONTH(Daterangeday).
Drag and drop Occurrences from the Tables (Measure Names) list in the Data pane and drop the entry in the field next to Rows. The value is automatically converted to SUM(Occurrences).
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select Duplicate from the Sheet 1 tab context menu to create a second sheet.
Select Rename from the Sheet 1 tab context menu to rename the sheet to Graph.
Select Rename from the Sheet 1 (2) tab context menu to rename the sheet to Data.
Ensure that the Data sheet is selected. In the Data view:
Select Show me at the top right and select Text table (upper left top visualization) to modify the content of the Data view to a table.
Drag MONTH(Daterangeday) from Columns to Rows.
Modify Standard to Entire View from the Fit dropdown menu in the toolbar.
Your Tableau Desktop should look like below.
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Select New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Graph sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Data sheet from the Sheets shelf below the Graph sheet onto the Dashboard 1 view.
Select the Data sheet in the view and modify Entire View to Fix Width.
Your Tableau Desktop should look like below.
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Single dimension ranked
In this use case, you want to display a table and simple bar visualization that shows the purchases and purchases revenue for product names over 2023.
Customer Journey Analytics
An example Single Dimension Ranked panel for the use case:
You see an empty table displaying only the column headers for the selected element. For better visibility, enlarge the visualization.
In the Filters pane:
Select the daterange is (All) from Filters on this visual.
Select Relative date as the Filter type.
Define the filter to Show items when the valueis in the last1calendar years.
Select Apply filter.
You see the table updated with the applied daterange filter.
In the Visualization pane:
Use
to remove daterange from Columns.
Drag and drop Sum of purchases_revenue underneath Sum of purchases in Columns.
On the Table visualization:
Select Sum of purchase_revenue to sort the product names in descending purchase revenue order. Your Power BI Desktop should look like below.
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In the Filters pane:
Select product_name is (All).
Set Filter type to Top N.
Define the filter to Show itemsTop10By value.
Drag and drop purchase_revenue into By valueAdd data fields here.
Select Apply filter.
You see the table updated with values for purchase revenue in sync with the Freeform table visualization in Analysis Workspace.
In the Visualizations pane:
Select the Line and stacked column chart visualization.
A line and stacked column chart visualization replaces the table while using the same data as the table.
Drag and drop purchases onto Line y-axis in the Visualizations pane.
The line and stacked column chart is updated. Your Power BI Desktop should look like below.
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On the Line and stacked column chart visualization:
Select
.
From the context menu, select Show as a table.
The main view is updated to show both a line visualization and a table.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates and specify a period of 01/01/2023 - 31/12/2024. Select Apply and OK.
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Drag and drop Product Name from the Tables list in the Data pane and drop the entry in the field next to Rows.
Drag and drop Purchases from the Tables (Measure Names) list in the Data pane and drop the entry in the field next to Rows. The value is automatically converted to SUM(Purchases).
Drag and drop Purchase Revenue from the Tables (Measure Names) list in the Data pane and drop the entry in the field next to Columns and left from SUM(Purchases). The value is automatically converted to SUM(Purchase Revenue).
To order both charts in descending purchase revenue order, hover over the Purchase Revenue title and select the sort icon.
To limit the number of entries in the charts, select SUM(Purchase Revenue) in Rows and from the dropdown menu select Filter.
In the Filter [Purchase Revenue] dialog select Range of values and enter appropriate values. For example: 1,000,000 - 2,000,000. Select Apply and OK.
To convert the two bar charts to a dual combination chart, select SUM(Purchases) in Rows and from the dropdown menu, select Dual Axis. The bar charts transform into a scatter plot.
To modify the scatter plot to a bar chart:
Select SUM(Purchases) in the Marks area and select Line from the dropdown menu.
Select SUM(Purchase Revenue) in the Marks area and select Bar from the dropdown menu.
Your Tableau Desktop should look like below.
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Select Duplicate from the Sheet 1 tab context menu to create a second sheet.
Select Rename from the Sheet 1 tab context menu to rename the sheet to Data.
Select Rename from the Sheet 1 (2) tab context menu to rename the sheet to Graph.
Ensure that the Data sheet is selected.
Select Show me at the top right and select Text table (upper left top visualization) to modify the content of the two charts to a table.
To order purchase revenue in descending order, hover over Purchase Revenue in the table and select
.
Select Entire View from the Fit dropdown menu.
Your Tableau Desktop should look like below.
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Select New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Graph sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Data sheet from the Sheets shelf below the Graph sheet onto the Dashboard 1 view.
Select the Data sheet in the view and modify Entire View to Fix Width.
Your Dashboard 1 view should look like below.
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Multiple dimension ranked
In this use case, you want to display a table that breaks down the purchase revenue and purchases for product names within product categories over 2023. On top of that you want to use some visualizations to illustrate both the product category distribution and product name contributions within each product category.
Customer Journey Analytics
An example Multiple Dimension Ranked panel for the use case:
To ensure the date range apply to all visualizations, drag and drop daterangeday from the Data pane on to Filters on this page.
Select the daterangeday is (All) from Filters on this page.
Select Relative date as the Filter type.
Define the filter to Show items when the valueis in the last1calendar years.
Select Apply filter.
In the Data pane:
Select datarangeday.
Select product_category.
Select product_name.
Select β purchase_revenue
Select β purchases
To modify the vertical bar chart to a Table, ensure you have the table selected and select Matrix from the Visualizations pane.
Drag product_name from Columns and drop the field underneath product_categor y in Rows in the Visualization pane.
To limit the number of displayed products within the table, select product_name is (All) in the Filters pane.
Select Advanced filtering.
Select Filter typeTop NShow itemsTop15By Value.
Drag purchases from the Data pane onto the Add data fields here.
Select Apply filter.
To improve readability, select View from the top menu, and select Page View > Actual size and resize the table visualization.
To break down each category in the table, select + at the product category level. Your Power BI Desktop should look like below.
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Select Home from the top menu, and select New visual. A new visual is added to your report.
In the Data pane:
Select product_category.
Select product_name.
Select purchase_revenue.
To modify the visual, select the bar chart and select Treemap from the Visualizations pane.
Ensure that product_category is listed underneath Category, and product_name is listed underneath Details in the Visualizations pane.
Your Power BI Desktop should look like below.
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Select Home from the top menu, and select New visual. A new visual is added to your report.
In the Data pane:
Select product_category.
Select purchase_revenue.
Select purchase.
In the Visualizations pane:
To modify the visualization, select Line and stacked column chart.
Drag sum_of_purchases from Column y-axis to Line y-axis.
In the report, reshuffle the individual visualizations.
Your Power BI Desktop should look like below.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Relative dates, select Years, and specify Previous year. Select Apply and OK.
Your Tableau Desktop should look like below.
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Drag Product Category and drop next to Columns.
Drag Purchase Revenue and drop next to Rows. The value changes to SUM(Purchase Revenue).
Drag Purchases and drop next to Rows. The value changes to SUM(Purchases).
Select SUM(Purchases) and from the dropdown menu select Dual Axis.
Select SUM(Purchases) in Marks and select Line from the dropdown menu.
Select SUM(Purchase Revenue) in Marks and select Bar from the dropdown menu.
Select Entire View from the Fit menu.
Select the Purchase Revenue title in the chart and ensure that the purchase revenue is in ascending order.
Your Tableau Desktop should look like below.
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Rename the current Sheet 1 sheet to Category.
Select New Worksheet to create a new sheet, and rename it to Data.
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Relative dates, select Years, and specify Previous year. Select Apply and OK.
Drag Purchase Revenue from Data pane to Columns. The value changes to SUM(Purchase Revenue).
Drag Purchase from Data pane to Columns, next to Purchase Revenue. The value changes to SUM(Purchases).
Drag Product Category from the Data pane to Rows.
Drag Product Name from the Data pane to Rows, next to Product Category.
To change the two horizontal bars to a table, select Text Table from Show Me.
To limit the number of products, select Purchases in Measure Values. From the dropdown menu, select Filter.
In the Filter [Purchases] dialog, select At least and enter 7000. Select Apply and OK.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
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Select New worksheet to create a new sheet and rename it to Treemap.
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filters Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Relative dates, select Years, and specify Previous year. Select Apply and OK.
Drag Purchase Revenue from the Data pane to Rows. The values changes to SUM(Purchase Revenue).
Drag Purchase from the Data pane to Rows, next to Purchase Revenue. The value changes to SUM(Purchases).
Drag Product Category from the Data pane to Columns.
Drag Product Name from the Data pane to Columns.
To change the two vertical bar charts to a treemap, select Treemap from Show Me.
To limit the number of products, select Purchases in Measure Values. From the dropdown menu, select Filter.
In the Filter [Purchases] dialog, select At least and enter 7000. Select Apply and OK.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
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Select New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Category sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Treemap sheet from the Sheets shelf underneath the Category sheet on the Dashboard 1 view.
Drag and drop the Data sheet from the Sheets shelf underneath the Treemap sheet on the Dashboard 1 view.
Resize each of the sheets in the view.
Your Dashboard 1 view should look like below.
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Count distinct dimension values
In this use case, you want to get the distinct number of product names that have been reported on during January 2023.
Customer Journey Analytics
To report on a distinct count of product names, you set up a calculated metric in Customer Journey Analytics, with TitleProduct Name (Count Distinct) and External Idproduct_name_count_distinct.
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You then can use that metric in an example Count Distinct Dimension Values panel for the use case:
To ensure the date range apply to all visualizations, drag and drop daterangeday from the Data pane on to Filters on this page.
Select the daterangeday is (All) from Filters on this page.
Select Advanced filtering as the Filter type.
Define the filter to Show items when the valueis on or after1/1/2023Andis before2/1/2023.
Select Apply filter.
In the Data pane:
Select datarangeday.
Select β cm_product_name_count_distinct, which is the calculated metric defined in Customer Journey Analytics.
To modify the vertical bar chart to a Table, ensure you have the chart selected and select Table from the Visualizations pane.
Your Power BI Desktop should look like below.
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Select the table visualization. From the context menu, select Copy > Copy visual.
Paste the visualization using ctrl-v. The exact copy of the visualization overlaps the original one. Move it to the right in the report area.
To modify the copied visualization from a table to a card, select Card from Visualizations.
Your Power BI Desktop should look like below.
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Alternatively, you can use the count distinct functionality from Power BI.
Select the product_name dimension.
Apply the Count (Distinct) function on the product_name dimension in Columns.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange entry from the Tables list in the Data pane and drop the entry onto the Filters shelf.
In the Filter Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates, and select 01/01/2023 - 31/1/2023. Select Apply and OK.
Drag Cm Product Name Count Distinct to Rows. The value changes to SUM(Cm Product Name Count Distinct). This field is the calculated metric that you have defined in Customer Journey Analytics.
Drag Daterangeday and drop next to Columns. Select Daterangeday and from the dropdown menu select Day.
To modify the lines visualization to a table, select Text Table from Show Me.
Select Swap Rows and Columns from the toolbar.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
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Select Duplicate from the Sheet 1 tab context menu to create a second sheet.
Select Rename from the Sheet 1 tab context menu to rename the sheet to Data.
Select Rename from the Sheet 1 (2) tab context menu to rename the sheet to Card.
Ensure you have selected the Card view.
Select DAY(Daterangeday) and from the dropdown menu select Month. The value changes to MONTH(Daterangeday).
Select SUM(Cm Product Name Count Distinct) in Marks and from the dropdown menu select Format.
To change the font size, in the Format SUM(CM Product Name Count Distinct) pane, select Font within Default and select 72 for the font size.
To align the number, select Automatic next to Alignment and set Horizontal to centered.
To use whole numbers, select 123.456 next to Numbers and select Number (Custom). Set Decimal places to 0.
Your Tableau Desktop should look like below.
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Select New Dashboard tab button (at the bottom) to create a new Dashboard 1 view. In the Dashboard 1 view:
Drag and drop the Card sheet from the Sheets shelf onto the Dashboard 1 view that reads Drop sheets here.
Drag and drop the Data sheet from the Sheets shelf underneath the Card sheet on the Dashboard 1 view.
Your Dashboard 1 view should look like below.
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Alternatively, you can use the count distinct functionality from Tableau Desktop.
Use Product Name instead of Cm Product Name Count Distinct.
Apply Measure > Count (Distinct) on Product Name in Marks.
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Use date range names to filter
In this use case you want to use a date range that you have defined in Customer Journey Analytics to filter and report on occurrences (events) during the last year.
Customer Journey Analytics
To report using a date range, you set up a date range in Customer Journey Analytics, with TitleLast Year 2023.
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You then can use that date range in an example Using Date Range Names To Filter panel for the use case:
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Note how the date range defined in the Freeform table visualization overrules the date range applied to the panel.
You see a visualization displaying Error fetching data for this visual.
In the Filters pane:
Select the daterangeName is (All) from Filters on this visual.
Select Basic filtering as the Filter type.
Underneath the Search field, select Last Year 2023, which is the name of your date range defined in Customer Journey Analytics.
Select
to remove daterangeName from Columns.
You see the table updated with the applied daterangeName filter. Your Power BI Desktop should look like below.
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Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Daterange Name entry from the Tables list in the Filters shelf.
In the Filter [Daterange Name] dialog ensure Select from list is selected, and select Last Year 2023 from the list. Select Apply and OK.
Drag Daterangemonth entry from the Tables list and drop the entry in the field next to Rows⦠Select Daterangemonth and select Month. The value changes to MONTH(Daterangemonth).
Drag Occurrences entry from the Tables list and drop the entry in the field next to Columns⦠The value changes to SUM(Occurrences).
Select Text Table from Show Me.
Select Swap Rows and Columns from the toolbar.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
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Use filter names to filter
In this use case, you want to use an existing filter for the Fishing product category, that you have defined in Customer Journey Analytics, to filter and report on product names and occurrences (events) during January 2023.
Customer Journey Analytics
Inspect the filter that you want to use in Customer Journey Analytics.
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You then can use that filter in an example Using Date Range Names To Filter panel for the use case:
You see a visualization displaying Error fetching data for this visual.
In the Filters pane:
Select filterName is (All) from Filters on this visual.
Select Basic filtering as the Filter type.
Underneath the Search field, select Fishing Products, which is the name of the existing filter defined in Customer Journey Analytics.
Select daterange is (All) from Filters on this visual.
Select Advanced filtering as the Filter type.
Define the filter to Show items when the valueis on or after1/1/2023Andis before2/1/2023.
Select
to remove filterName from Columns.
Select
to remove daterange from Columns.
You see the table updated with the applied filterName filter. Your Power BI Desktop should look like below.
{modal="regular"}
Tableau Desktop
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Filter Name entry from the Tables list in the Filters shelf.
In the Filter [Filter Name] dialog ensure Select from list is selected, and select Fishing Products from the list. Select Apply and OK.
Drag Daterange entry from the Tables list in the Filters shelf.
In the Filter Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates, and select 01/01/2023 - 01/02/2023. Select Apply and OK.
Drag Product Name from the Tables list to Rows.
Drag Occurrences entry from the Tables list and drop the entry in the field next to Columns⦠The value changes to SUM(Occurrences).
Select Text Table from Show Me.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
{modal="regular"}
Use dimension values to filter
You create a new filter in Customer Journey Analytics that filters on products from the hunting product category. Then you want to use the new filter to report on product names and occurrences (events) for products from the hunting category during January 2023.
Customer Journey Analytics
Create a new filter with TitleHunting Products in Customer Journey Analytics.
{modal="regular"}
You then can use that filter in an example Using Dimension Values To Filter panel for the use case:
Select Home from the menu, then select Refresh from the toolbar. You need to refresh the connection to pick up the new filter you just defined in Customer Journey Analytics.
In the Data pane:
Select daterange.
Select filterName.
Select product_name.
Select β occurrences.
You see a visualization displaying Error fetching data for this visual.
In the Filters pane:
Select filterName is (All) from Filters on this visual.
Select Basic filtering as the Filter type.
Underneath the Search field, select Hunting Products, which is the name of the existing filter defined in Customer Journey Analytics.
Select daterange is (All) from Filters on this visual.
Select Advanced filtering as the Filter type.
Define the filter to Show items when the valueis on or after1/1/2023Andis before2/1/2023.
Select
to remove filterName from Columns.
Select
to remove daterange from Columns.
You see the table updated with the applied filterName filter. Your Power BI Desktop should look like below.
{modal="regular"}
Tableau Desktop
In the Data Source view, underneath Data, from the context menu on cc_data_view(prod:cja%3FFLATTEN), select Refresh. You need to refresh the connection to pick up the new filter you just defined in Customer Journey Analytics.
Select the Sheet 1 tab at the bottom to switch from Data source. In the Sheet 1 view:
Drag the Filter Name entry from the Tables list in the Filters shelf.
In the Filter [Filter Name] dialog ensure Select from list is selected, and select Hunting Products from the list. Select Apply and OK.
Drag Daterange entry from the Tables list in the Filters shelf.
In the Filter Field [Daterange] dialog, select Range of Dates and select Next >.
In the Filter [Daterange] dialog, select Range of dates, and select 01/01/2023 - 1/2/2023. Select Apply and OK.
Drag Product Name from the Tables list to Rows.
Drag Occurrences entry from the Tables list and drop the entry in the field next to Columns⦠The value changes to SUM(Occurrences).
Select Text Table from Show Me.
Select Fit Width from the Fit dropdown menu.
Your Tableau Desktop should look like below.
{modal="regular"}
Sort
In this use case, you want to report on purchase revenue and purchases for product names during January 2023, sorted in descending purchase revenue order.