September 21, 2017

Date Filters: Improvements in Custom and Fiscal Calendars

We have made a few improvements in how date filters work with custom calendars and fiscal calendars.

>> DATES FOR SELECTED GRANULARITY
When you are selecting granularity (week, month, quarter...) in a date filter on your dashboard, the dates for the granularity are now displayed according to your custom calendar or fiscal calendar, not to the standard Gregorian calendar.

Example: Your fiscal month starts on the last day of the previous month (that is, your fiscal month for April starts on March 31, and so on). If you select April for your date filter, it now shows March 31 - April 29. Before, it showed April 1 - April 30.

     Dates_for_selected_granularity.png

>> PREVIEW FOR SELECTED GRANULARITY
When you are adding a date filter to a dashboard and are setting granularity for the filter, the preview panel now shows the name of the selected granularity according to your custom calendar or fiscal calendar, not to the standard Gregorian calendar.

Example: Your fiscal year starts on April 1, so the period from July through September is the second quarter of the year. If your default date range is “Quarter” and you select “this” on, let’s say, on August 17, the preview shows Q2. Before, it showed Q3.

     Preview_for_selected_granularity.png

>> KNOWN LIMITATIONS
Consider the following known limitations applied to the improvements in custom calendars and fiscal calendars for date filters:

  • The Report Editor, Analytical Designer and KPI dashboards do not support custom or fiscal date dimensions.
  • The calendar available under the date picker in a date filter shows the standard Gregorian calendar. However, you can hide the calendar icon -- see the next article in these Release Notes.

 

Date Filters: Hide and Show Date Picker

By default, a date filter lets you either select the date using the calendar icon, or manually enter the dates in the “From” and “To” fields.

     Hide_show_date_picker_1.png


When you are adding a date filter to a dashboard, you can configure it to either hide the calendar icon only (so the users can still enter the dates in the “From” and “To” fields manually), or hide the whole date range selection (users can select the range only from the scrolling timeline):

     Hide_show_date_picker_2.png


This is how a user will see the date filter when the calendar icon is hidden (you selected the option Hide calendar from date range selection):

     Hide_show_date_picker_3.png


This is how a user will see the date filter when the whole date range selection is hidden (you selected the option Hide “From/To” date range selection):

     Hide_show_date_picker_4.png

 

Learn more:
Date Filters

 

Date Filters Named after Date Datasets

We have changed the way how the date filters are named when added to a dashboard.
Date_filter_name.png

What exactly has changed?
Before, when you were adding a date filter to a dashboard, the filter was automatically named after the date dimension that it is based on.
Now, the newly added date filter is named after the date dataset that is it based on.

Nothing changes for existing date filters!
This change does not affect the date filters that already exist on your dashboards. It only applies to the date filters that you add in the future.

What can you check before adding any new filters?
From the GoodData Portal, go to Manage -> Data -> Data Sets, and check the names of the date datasets in your project. Keeping in mind that the dataset names are now used as names for all new date filters, decide whether you want to rename any dataset to make sense once their names are used as filter names.

NOTE: You still can rename a date filter on your dashboard at any time.

Learn more:
Filter for Dates

 

Delete Old Data while Loading New Data via API or CloudConnect

When loading new data to a dataset via CloudConnect or API, you can now delete old data from the same or different dataset.

Deleting data from and uploading data to a dataset are done in a single transaction. This helps keep data in your project consistent and avoid situations when new data is already in the dataset but the old data are not yet removed from it. Using this feature, you can build better performing data pipelines that include data deletion.

Learn more:
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