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Data sources

first stepstile editor

Tile Editor

The tile editor is the interface that lets you retrieve, filter, shape and visualize your data. You use the tile editor whenever you want to add or edit a data tile, or when when using the data explorer to experiment with your data streams.

You can add a title and description for your tile at the top of editor.

Configuration flow

The steps for configuring a data tile may vary depending on which data stream you select, however the configuration flow usually remains similar.

To configure a tile, you work down the tabs of the tile editor to retrieve, filter and shape the data you want and then use the panel on the right-hand side of the page to configure the Visualization, Monitoring and KPI settings.

The steps to configuring a tile can include:

  1. Selecting a data stream
  2. Selecting objects
  3. Configuring parameters
  4. Specifying a timeframe
  5. Shaping data
  6. Formatting data columns

Data stream

The first step to visualizing your data is to choose the data stream you want to use. Therefore, when you add a new data tile to a dashboard, you are presented with the data stream splash screen.

From here, you can quickly select recent data stream to display data streams for. If the data stream you need isn't immediately presented, then click either the Data Stream tab on the left or the Browse all data streams button to expand the data stream tab.

Data streams list

The Data Stream tab displays a list containing all of data streams for your currently indexed data sources and can be filtered using the search and dropdowns.

For each data stream in the list you will see:

  • The Name of the data stream. You you can sort data by streams A-Z or Z-A by clicking thiscolumn.
  • A Description of the data stream.
  • The Type of object that the data stream is available for (matches).
  • Featured data streams, indicated by the flame icon
    , which contextually include data streams which might be the most important or most useful.
  • Recently used data streams, indicated by a clock icon
    , are floated to the top of the list for easy access.

The data streams list with the most recently used streams floated to the top

Many data streams related to each other as pre-configurations of an encompassing data stream.

For example, the Workflow Runs / In Progress Worklows data stream is a pre-configuration of the Workflow Runs data stream, where the Status parameter has automatically been pre-selected.

To reflect this, pre-configured data streams follow the naming convention of <Primary data stream> / <pre-configuration>.

For help with configuring the data streams specific to your data source, refer to the corresponding data source article:

List of documentation for data source plugins available

Objects

Use the Objects tab of the tile editor to specify a collection of objects to display data for. You only need to complete this tab if you have selected a Scoped data stream.

Selecting a collection

Do the following to choose the objects for the collection:

  1. Search the list for the objects for those you want to add. By default, every object you have access to is presented with the total selected / available displaying below.
    • Use the the Search objects box to directly search for objects by their name.
    • Use the Filter pane on the left-hand side to select the Data source(s),Types and / or Collections to filter the object list by.
      • Click Add filter
        at the bottom of the Filter pane to add additional properties to the filter list.
        When you add a filter it also adds that property as a column in the object list so you can see the values.
        You can also achieve this by clicking the Add column button
        at the top right.
  2. To select the objects you wish to be in the collection you can either tick the objects, or toggle the Dynamic selection button.

    • Fixed selection: Returns the specific objects that you manually pick by ticking them. Objects in a fixed scope never change, except when you edit the collection.
    • Dynamic selection: Enabled by selecting the Dynamic selection toggle this returns all the objects that match the criteria specified in the Filter panel and search. When objects that match are added to or removed from SquaredUp, the objects in the selection will change. Dynamically scoped tiles check which objects match the filter whenever they refresh.

  3. Click Next.

Saving a collection

The collection of objects you specify on this tab can be saved for future use in your workspace by clicking Add collection

in the Filter panel. This opens the Add collection window, pre-populated with the objects you selected.

Collections can also be created and saved via the Objects page, accessed via the left-hand menu. See Collections.

Parameters

Use the Parameters tab of the tile editor to configure your data streams. Not every data stream has parameters to configure (for example, a data stream might simply retrieve a specific set of data), and those that are can vary widely depending on the data stream itself.

For instructions of configuring the parameters for a data stream, refer to the Data streams section for the corresponding plugin.

Timeframe

Use the Timeframe tab to choose the timeframe that a tile displays data for. For example, by default a tile's timeframe is set to the dashboard timeframe but you could instead choose to display data from the last 30 days.

No timeframe option

There are many data streams where specifying a timeframe is optional, such as ones which scope to a specific collection and thus don't necessarily need to return results from a specific period.

In these circumstances, the timeframe picker displays the None option, allowing you to return results without considering the tile / dashboard timeframe.

If None is the selected option for the timeframe:

  • The Timeframe tab in the tile editor shows None.
  • No tile timeframe pill displays on the tile.
  • When enabling monitoring or KPI, no timeframe is enforced on the tile (such as when using dashboard timeframe).

Mandatory timeframes

Many data streams, particularly those that accept a query input such as KQL, require you to specify a timeframe. In such cases, the Timeframe tab is not shown and the timeframe must be declared in on the Parameters tab.

Timeframe not supported

In circumstances where specifying a timeframe for a data stream is not supported, the Timeframe tab is not shown.

Referencing the timeframe

When setting a timeframe for some data streams, you will be required to reference the timeframe on the Parameters tab - typically such as when configuring custom queries or requests.

To do this, you can enter {{timeframe.start}} and {{timeframe.end}} in your query or request as appropriate. These two values represent the start and end of the currently selected timeframe in ISO format (for example, 2025-05-19T11:44:57.000Z).

These Mustache-style placeholders support JavaScript, allowing you to format values dynamically based on your needs.

Shaping

Data shaping lets you transform and structure your raw data to improve clarity and usability before visualizing it. This process involves:

  • Filtering, which extracts relevant subsets by applying conditions.
  • Grouping, which aggregates data based on common attributes.
  • Sorting, which arranges data in ascending or descending order.

Filtering

Data can be filtered according to whether data in a column meets or does not meet specified text or numerical value conditions.

Multiple filters

You are able to add multiple filter conditions using the following operators:

  • AND: All conditions must be satisfied (e.g. Status-Equals-Closed ANDType-Equals-Question).
  • OR: Any condition can be satisfied (e.g. Status-Equals-Pending ORStatus-Equals-Closed).

Available filters

The following options are available when filtering data, which ones display depends on the column type.

Option
Description
Equals
Checks if the value of a field is the same as the specified value. For example,a Status of Active will return results where the status is Active.
Not equals
Checks if the value of a field is not equal to the specified value. It returns true if the values are different. For example, a status of Active would return results where the category is notActive.
Contains
Returns data if the specified value exists within the field value.
For example, example: URL Contains projects will return results where the URL includes the word "projects" anywhere in the string.
Doesn't contain
Returns data if the specified value doesn't exist within the field value.
For example, example: URL Doesn't contain projects will return results where the URL doesn't include the word "projects" anywhere in the string.
Less than
Checks if the value of a field is below the specified value. It is used for numerical or date values. For example, IncidentsLess than50 would return results where the number of incidents is below 50.
Greater than
Checks if the value of a field is over a specified value. It is used for numerical or date values. For example, Incidents Greater than 50 would return results where the number of incidents is over 50.
Is more than
Available when working with a date / time column. Checks if the value of a field is older than a given time period. You must additionally specify a time quantity and period, and whether to measure ago or from now.
For example, Due Is more than 100 days from now will return results where the due date is later than the current day + 100 days.
Similarly, Due Is more than 100 days ago will return results where the submitted date is earlier than the current day.
Within last
Filter records that fall within a specific time range from before the current date and time. You must additionally specify a time quantity and period.
For example, Submitted Within last 100 days will return results where the submitted date is between the current day and 100 days ago.
Within next
Filter records that are within a specified time range after the current date and time. You must additionally specify a time quantity and period.
For example, Event date Within next 7 days would return results where the event date is within the next week.
Is empty
Returns all data without a date value. Useful for identifying records where data is missing.
Is not empty
Returns all data with a date value.

Grouping

Use the grouping section to group and aggregate data columns.

For example, for AWS cost data you might configure the following settings to display a table or bar chart of cost per label:

  • Group by:label
  • Aggregation type: Total
  • Aggregation column: Amount

Which columns are available depends on the data stream you chose.

Configuring grouping enables different visualizations to be displayed, such as bar chart and donut. For example, grouping tickets by channel allows you to show a donut of how many tickets were logged by email vs web form.

Bucket by

If you group by a time column, and further grouping is possible, the Bucket by dropdown appears. Use this field to control how the time data is grouped, for example by hour, day, month etc.

Aggregation

To aggregate your data, you must select an Aggregation type and a target Aggregation column. For example, if creating bar chart for an Azure Resource Group cost, you could configure the following settings:

  • Group by: Timestamp
  • Bucket by: Day
  • Aggregation type: Total
  • Aggregate column: Cost

The following lists the available aggregation types.

Aggregate
Description
Total
Sums up all numerical values in a dataset, providing the overall total
Average
Calculates the mean by dividing the total sum by the number of values
Count
Determines the number of entries in a dataset, including duplicates
Distinct Count
Counts only unique values, ignoring duplicates
Max
Identifies the highest value in a dataset
Median
Finds the middle value when data is sorted in ascending order
Min
Identifies the lowest value in a dataset
Mode
Determines the most frequently occurring value in a dataset

Sorting

The Sort section allows you to select one or more columns to sort your date by, in either ascending or descending order.

While this sets the default sort order of data, but you can always click on a column heading to sort the data table on the fly.

To sort by multiple columns, click Add sort by to add a new row of sort fields to the list. This allows you perform more complex sorts, such as sorting data by the data it was created, then sorting those results alphabetically.

Enabling the Top toggle allows you to specify the top n rows of data to display.

Columns

Use the Columns tab of the tile editor to format the columns of the table on the Data tab.

SquaredUp automatically defines the metadata retrieved from data streams so the data is assigned the correct data type, however in some circumstances you may want to override this.

For example, when retrieving data using the Web API plugin, scripting, or custom query data streams (such as Splunk Enterprise plugin), the assigned data type may not be quite correct or as you expect.

Formatting columns

Use the following options to format your columns.

Option
Description
Name
To rename a column, click the current Name value and enter a new one. Columns that can be renamed display the Rename column icon
when hovered over.
Type
Select an option from the Type dropdown to change the data type of the column. If any additional options are available to configure, the dropdown is expanded below.
Value
Displays the original value of the column.
Formatted
Displays the formatted value of the column.
Add a copy of this column
Click to duplicate a column. The copied field displays Copy of [field name] above its Name.
Remove this column
Click to delete a cloned column.

Comparison columns

Comparison columns are used to compare two values, for example you may want to compare the number of tickets raised this month to the number of tickets raised last month. You can choose to show the value as an absolute change (for example, 12 more tickets) or as a percentage change (for example, a 28% increase).

When a column has a Type of Number, the Add comparison

button displays at the end of the row, which you can click to open the Add comparison window.
From this window, if you have multiple columns with a Type of Number, you can create a comparison column by doing the following:

  1. Column A:
    Select the first column to compare against. Automatically populated with the column of which you clicked Add comparison
    .
  2. Column B:
    Select the second column to compare against.
  3. Output:
    Select how to display the comparison value. This value is displayed in the Preview field. Choose from:
    • Absolute: Show the numerical value of Column A - Column B.
    • Percentage: Show the ratio of Column B to Column A as a percent.
  4. Click Add to create the comparison.

Additional options

Some data types have advanced settings that can be configured in the options section, which is displayed whenever you change the data Type or by clicking expand

next to the column Name.

Option
Description
Output Format
Enter a custom format to display date values as a string. Any specified output format is supported. For example, dd/mm/yy, dd/mm/yyyy or d/M/Y.

By default, dates and times are displayed in your local timezone to ensure the data makes sense to you.

Input Format
Enter the format that corresponds to the inputted date. For example, if your data has values such as 05/27/24 01:44 PM, then the Input Format should be set to dd/mm/yy hh:mm aa.
Any input format is supported, however if you have a custom input format that is missing any time zone information, the input is always assumed to be UTC.

This field is required if the data string for the column are not ISO-8601 formatted. For example, 2024-09-09T13:52:25.281Z.

Currency
Select the currency to display the value in. This does not convert the currency value.
Decimal Places
Formats the number of decimal places for a supported data type. Enter a value between 0 and 20.
Link Text
Specify the text of the URL links in the column.
Format as duration
Toggle between displaying the time value in minutes and seconds or seconds.
Map Values to States

You can map the states you're getting back from your data to the states SquaredUp expects.

SquaredUp expects the following values for states to be able to show Status Blocks in the correct matching color:

success
green
warning
yellow
error
red
unknown
gray

If your data uses different values for states, you can map them to the values SquaredUp expects.

Tip: Any state value that SquaredUp doesn't recognize gets automatically set to unknown. You can usually just leave out the unknown state from your mapping and just specify the other three states.

Visualization

Visualization settings are configured on the Visualization tab of the right-hand panel in the tile editor.

Which visualizations are offered to you depends on the data available, for example Line Graph will only be offered if there is time series data in your dataset.

For detailed information on configuring each visualization type, see Visualizations.

These steps describe the simple tile editor. Advanced users might like to try the SQL Analytics editor see SQL Analytics (Beta).

Monitoring

You can enable and create monitors for your data tiles on the Monitoring tab of the tile editor.

These monitors let you watch for changes to your configured data and trigger notifications and status rollups whenever a state, threshold or scripted condition is met.

For detailed information on configuring monitoring, see Monitors.

KPI

KPIs can publish key metrics within a workspace and also aggregate at a higher level for complete oversight.

Defining, monitoring and evaluating KPIs is a practice followed by virtually every organization. In your organization there may be KPIs such as DORA metrics, Service Level Objectives or Cloud costs. SquaredUp allows you to visualize, monitor, and roll-up these values - giving you complete oversight of your key metrics.

KPIs are enabled and configured on the KPI tab of the tile editor.

For detailed information on configuring KPIs, see KPIs.

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On this page

  • Configuration flow
  • Data stream
  • Data streams list
  • Objects
  • Selecting a collection
  • Saving a collection
  • Parameters
  • Timeframe
  • No timeframe option
  • Mandatory timeframes
  • Timeframe not supported
  • Referencing the timeframe
  • Shaping
  • Filtering
  • Grouping
  • Sorting
  • Columns
  • Formatting columns
  • Comparison columns
  • Additional options
  • Visualization
  • Monitoring
  • KPI

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