Table of Contents
Updated by Tara
JRNI Analytics Plus gives you the power to create and customize your own reports and visualizations. You can then distribute these to other members of the business or add them to one of your dashboards.
Key report building / data exploration concepts
Before you begin creating your own reports, it’s important to familiarize yourself with the key concepts used to explore data/build reports:
- Dimensions (groups/buckets of data): These are columns of your data that are physical (columns in the database) or logical (such as a calculation or translation of actual data).
- Measures (information about the group/bucket of data): Aggregations and calculations across one or many rows, such as a sum, minimum, maximum, or average.
- Filters (used to limit data): These behave differently depending on whether you are filtering a dimension or a measure.
- Pivots (used to break a dimension into columns): Using pivots allows you to see the distinct groups of a dimension displayed as horizontal columns.
Key report building components on the Explore page
- (1) Field search: Here you can search from the full list of fields for a specific dimension or measure.
- (2) Field picker: Expand the fields broken down into categories/sections to look for an appropriate dimension or measure. All the same fields available in the full list can be found here.
- (3) Filters: This section is where you can apply filters to help narrow down the data pulled into your report.
- (4) Visualization: This section allows you to choose from different visualization types (e.g tables, graphs and maps) to present your data.
- (5) Data: Columns of the data returned from the selected fields. You can also add some extra calculations/logic via the calculation button.
- (6) Run: This button will submit a query request and return data based on the selected field and filter options you have selected.
- (7) Calculations: Similar to formulas you might use on a spreadsheet, table calculations allow you to create metrics by performing calculations on your selected fields.
Creating a new report from the Explore menu
Using the steps below and key concepts mentioned above, we’ll start by a) adding Data using any dimensions/measures, b) adding Filters to narrow down the data displayed, and c) selecting a Visualization to present our data/report.
- Navigate to your JRNI Plus Analytics account.
- Click Explore from the top menu.
- From the dropdown, select a category that most relates to what you’re looking to understand from your report.
You will be presented with an empty report on the explore page, ready for you to start adding your own dimensions and measures to.
- Use the field search (search a specific field) or field picker (browse fields by category) to locate the dimensions/measures you wish to add to your report.
- Click a field (dimension or measure) to add it to the Data section of your report. Continue adding more as required. Quick Tip: Jump to the In Use tab to easily find what you’ve selected so far.
- Click the Run button from the top right corner to submit the query for your chosen data fields, and start previewing the results.
- Add a/multiple filters to narrow down the data displayed on your report. You can do this using the filter icon next to your dimension/measure from the field picker, or using the gear icon directly from the Data section.
- Customize your filter/s from the Filters section (appears once you click Filter on a specific dimension/measure). Click Run again to update your report and see your filters being applied.
- Click through the Visualization types to choose how you wish to present your data. Visualization types available will depend on the dimensions/measures added to your report.
- Check and set your preferred time zone in the top right corner. We recommend setting it “Viewer Time Zone (User)” (this will show the appropriate time zone according to the user’s location when viewing the report).
- When you have finished setting up your report as required, click the cog/gear icon from the top right to save your report:
- Save as a Look: which can later be added to any dashboards.
- Save to Dashboard: to add it to a specific dashboard. Note: if adding to a shared dashboard, it will be visible to all.
- Add a clear, descriptive title and description to explain the type of report/visualization you have created, and click Save.
Using Totals and Row Totals
Select the Totals option from the Data bar to display column totals for measure and Table Calculations. And/Or, if using pivots as per our example below, select Row Totals to display the sum of each row - use the arrow icon to shift the Row Totals between far left and right positions.
Use the pivot function to transpose a dimension from a singular row, into grouped columns (according to the data within the dimension). This is a valuable capability when you’re looking to break down elements of a dimension into groups.
In the following example, we’ll pivot the “booking category” dimension to enable us to view each of the categories as horizontal columns:
- Select a dimension from the field picker (in this example, Booking Details > Category) to add it to your report (or locate one already in use).
- Click the pivot icon from the field picker on the left (next to the dimension), or click the cog/gear icon.
The selected dimension will now transpose and appear as individual columns (according to the data), as highlighted in orange below.
You will likely see empty column fields at first, as the report requires that you add a measure to display data for your new category columns. For example, we might want to know the number of bookings for each of our new “booking category” columns, the number of cancellations etc…
Simply select a measure from the field picker and click the Run button.
- Sending, scheduling and downloading Reports/Dashboards
- Using Table Calculations
- Filtering Dashboard and Report data
Still have questions?
If you have additional questions about creating your own reports (Looks) or using JRNI Analytics Plus, please contact JRNI Customer Support, who will be happy to help.