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Navigate to the Table menu properties and click Date option Identify and highlight the dimension that you want to set as date, in our example it’s DimDate shown in Figure 9 Figure 9 In fact, the fix for a Tabular Model date source is much simpler. Resolving the issue when the connection is Tabular Model is very different from what we did for a Multidimensional source. The error displayed in Figure 3 could also be as a result of a PivotTable that is based off a Tabular Model. You should get an Insert Timelines dialog box similarly to that in Figure 8, indicating that Excel is finally able to detect your Multidimensional date dimensions.įigure 8: Insert Timeline from a Multidimensional cube Resolving Timeline Filter error when using Tabular Models When the processing of date dimension is complete, go back and refresh the excel workbook and try to add a Timeline filter again. Once you are done making changes into your Multidimensional mode, you can process the date dimension. Whatever fields you may have in your dimension, the trick is to always ensure that the ValueColumn property is set to an attribute that is defined as date.įigure 7: Configuring date key attributes
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Because we don’t have many attributes in our date dimension, both NameColumn and ValueColumn properties are set to Full Date Alternate Key. The final step involves configuring NameColumn and ValueColumn properties of your key attribute which are usually set to none by default. Setting dimension to time provides the capability of time based-levels of granularity i.e. The next step involves converting your date dimension to Time. Figure 5 shows the attributes of my date dimension, namely, Date Key as well as Full Date Alternate Key.įigure 5: Structure of my sample date dimension Open the date dimension and ensure that at the very least it contains two attributes, namely, an integer key attribute and a date attribute. Identify your date dimension, in our example, we are using Adventure Works’ DimDate shown in Figure 4 Figure 4: Multidimensional data source view Open your Multidimensional solution in SQL Server Data Tools (SSDT) The following is what you will have to do to fix the error when PivotTable is sourcing data from Multidimensional Cubes: Resolving Timeline Filter error when using Multidimensional Cubesįixing the Timeline error involves several steps. The reason for this error is because the Timeline filter is unable to detect any dimensions containing dates field in your PivotTable. If you have not properly configured your OLAP solution, then you are likely to run into error message “ We can’t create a Timeline for this report because it doesn’t have a field formatted as Date”, similar to what is shown in Figure 3. Multidimensional cubes, Tabular Model, and PowerPivot excel workbooks). This is in stark contrast to the traditional filter shown in line 1 of Figure 2 wherein it only indicates that multiple items have been chosen and the only way to understand on what those filter items are, is by clicking on the dropdown button.Īlthough the Timeline feature is a great control, getting it to work and correctly pick out date defined fields can be a frustrating task, particularly if your PivotTable is sourcing date from any of the SQL Server OLAP solutions (i.e. It also has useful annotations that describes what you have filtered on – in this case, we have chosen sales period between February and March 2011. Figure 1 illustrates one of those benefits whereby the Timeline filter allows end-users to easily apply a filter (i.e. The Timeline filter has several benefits compared to the traditional Excel dropdown filter. The Timeline filter control enables end users to visually filter Excel PivotTables using fields defined as dates. One such feature is the Timeline filter control which was first introduced in Microsoft Office 2013.
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Like many software products, newer version releases of Excel usually introduce new features. One of those data visualisation tools, is Microsoft Excel – which remains a popular data visualisations tool for many of my end users. These solutions have been consumed using numerous data visualisation tools. Over the course of my career, I have developed and deployed to production several business intelligence solutions.