How to Create Table-Based Analytics
How to Create Table-Based Analytics
Make an analysis based on a Table rather than an App
Analytics are a powerful way to display data collected on the shop floor. App-based Analytics are great for analyzing historical data. Table-based Analytics can be created in order to reflect the current state of a Table's fields and values.
Creating a Table Analysis
There are several routes a user can take to create a new Table Analytic:
- From the Dashboards page by pressing Add Analysis
- Navigate to the Table to create an analytic from, press the ellipsis icon, and select View Table Analyses
- From an application, embed an analysis, press Select an Analysis
These routes will lead to a common Add Analysis modal, where a user can select the Table data source from the left panel selector and pick the individual table to create an analysis on. Once the Table is selected, the option to Create Analysis can be performed.
Building a Table Analysis
The Analytic Editor used for Table Analyses is a similar experience to building analytics on apps or machines. Certain chart types may not be available depending on the data types stored in your Table.
The rest of the Analytics Editor will appear the same, but give options based on the current state of the table. The following options are present for Table Analytics:
Important Note: Date Range refers to the date and time the record was created.
X-Axis Time Scaling Options
The Date Created and Date Updated Metadata fields can now be used for creating analytics. Under the Date Range field, the Created At or Updated At field can be used to modify which of these fields is a reference to display data for the given analytic. The Created At Date is the default selection.
For analytics using the DateTime field as an X-axis, there is now an option to group the data using this dropdown -
In addition to this, under the Display dropdown, you can now choose the X-axis scaling. The Ordinal Scale evenly distributes the data in the UI while the time scale distributes the data based on the datetime value selected.
For the same data, here is how the two options compare:
Example 1 - Percent of Work Order Completion
In a table, you might store updated information on orders for the quantity ordered and quantity built. In a case such as this, a Table analysis can easily display these values. For example, the current state of the table might look something like this:
To analyze this data, you might want to see the current progress of these orders. To reiterate, the Analysis should be filtered to match the Date Range you are interested in based on when the ID was created in this table.
The X axis most usefully will display the name of the order, stored as the ID field.
The Y axis can then be made to compare the two number values of interest using an expression.
Here, the expression is simply dividing the number of made parts by the ordered value. It is then converting that number to a percentage.
This analysis will look something like this:
Example 2- Count of Statuses
You may want to check the current status of work orders. In this example, your work order status table might look something like this.
A count of the current statuses can be found most easily by setting the X axis to the Status field.
With Status selected, the Y axis should provide a count for how many records are in each Status. It might also be helpful to only provide the count where a value exists. To accomplish both at once, add a Count Where True aggregation to the Y axis. This will look something like this:
From here, you could provide more granular data by adding a Compare By field, perhaps based on the ID.
The outcome of this tracker will look something like this once completed:
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