What is a Data Stream?
Data streams standardize data from all the different shapes and formats your tools use into a straightforward tabular format. While creating a tile you can tweak data streams by grouping or aggregating specific columns. Depending on the kind of data, SquaredUp will automatically suggest how to visualize the result, for example as a table or line graph.
Data streams can be either global or scoped:
Global data streams are unscoped and return information of a general nature (e.g. "Get the current number of unused hosts").
A scoped data stream gets information relevant to the specific set objects supplied in the tile scope (e.g. "Get the current session count for these hosts").
How do I get Data Streams?
Pre-configured data streams - some data sources come with pre-configured data streams that are indexed when you add the data source.
Configurable data streams - some data sources allow you to create new data streams using a form.
A configurable data stream allows you to easily create new data streams specific to your needs, by entering information into a form, such as metric names or queries. Configurable data streams have a cog icon next to their name in the tile editor.
Advanced users can also write their own custom data streams (or edit a data stream created from a configurable data stream) see Custom Data Streams.
Using Data Streams
When adding or editing a tile on a dashboard you need to select a data stream, objects and visualization. See Dashboards
Help with configuring data streams specific to your data source can be found in each specific data source article:
See also Scripts
Data Stream Shaping
Data can be filtered according to whether data in a column meets or does not meet specified text or numerical value conditions. Depending on the data you are filtering, available options include: Equals, Not equals, Contains, Doesn't contain, Less than, Greater than, Before now, After now, Is empty, Is not empty.
Dates can be filtered by Before now or After now (e.g. to show overdue orders). Text matching is case sensitive.
You are able to add multiple filter conditions. Available options are:
AND – all conditions must be satisfied (e.g.
OR – any condition can be satisfied (e.g.
You can group and aggregate data by column.
For example, for AWS cost data you might Group by
label, choose Aggregation type
Total with Aggregation column
Amount, to show a table or bar chart of cost per label.
Which columns are available depends on the data stream you chose.
Configuring grouping will enable different visualizations to be displayed, such as bar chart and donut. For example, grouping tickets by channel will allow you to show a donut of how many tickets were logged by email vs web form.
If you group by a time column, and further grouping is possible, then the Bucket by dropdown will appear, which allows you to control how the time data is grouped, for example by
Aggregation type and column
Using this dropdown you can choose how to summarize your data, for example as a
For example, for a Bar Chart of ticket data you might Group by
Date created, choose Bucket by
Day with Aggregation type
Count, to show a line graph of tickets per day. Or for a Bar Chart of Azure Resource Group cost you might Group by
Timestamp, Bucket by
Day, Aggregation type
Total and Aggregate column
Data can be sorted by column in ascending or descending order. This sets the default sort order, but users can click on a column heading to sort data in a table on the fly.
Ticking Top and typing a number will show the top n rows of data.