SQL Analytics (Beta)
SQL Analytics allows you to carry out advanced manipulation of data using a SQL query before you visualize it.
For example:
You might ask 'What is the average time difference between a ticket created and resolved?' You can use SQL to calculate the difference between the ticket created and resolved time, then you can visualize the Mean Time To Resolution (MTTR).
For AWS CloudWatch data you might want to know 'What is the 95% percentile response time of my microservice?' use SQL to query the data, and then show the Service Level Indicator (SLI).
You can also combine entry points and query them before visualizing the data. You might combine your Azure Cost data with your Azure Monitor data and ask 'What is the potential cost saving of turning off my unused VMs?'
Switch to the Analytics Editor
When editing a tile, click on Enable SQL Analytics at the top of the screen. This changes your view from the simple tile editor into the more advanced SQL Analytics Editor. It's best to decide whether you want to stick with the SQL Analytics Editor for a particular tile, or with the simple editor, rather than switching between the two.
If you exit out of the SQL Analytics Editor, choosing to revert to using the simple editor for this tile, then you lose your SQL queries and datasets, as only the first dataset is saved.
As with the simple editor, you can still add Monitors or KPIs.
Datasets
A dataset is the data stream and selected objects combined. If you had already selected a data stream and objects in the simple tile editor, this will be shown as dataset1 and you will be taken straight to the SQL tab.
Datasets can be renamed by hovering over the tab of the dataset and clicking the pencil icon – hit Enter to save the change, hit Escape to cancel. For example, if you are looking at Zendesk tickets you might rename dataset1 to tickets.
The new name must be alphanumeric, with no spaces or punctuation. At the point of renaming, if the SQL query is unmodified, the name of the dataset is automatically updated in the SQL query.
You can add new datasets, allowing you to add in further data. For a new dataset, click + Add dataset and then configure the data stream and objects to show the data you want. A new tab appears with a sequential name – dataset2, dataset3, etc.
Each dataset can be configured to use a different timeframe, if required, or use the dashboard timeframe.
What is the dashboard timeframe?The dashboard timeframe is the current timeframe setting for a dashboard. Users can change the dashboard timeframe to see data for a different time span, for example, instead of showing data from "the last 12 hours" it can be changed to show data from "the last 7 days".
Tiles can be configured to:
Use dashboard timeframe (default). For these tiles the data shown will change when the user changes the dashboard timeframe.
Use a fixed timeframe from the options available. These tiles show a clock icon and hovering shows the fixed timeframe configured. The data will not change when the dashboard timeframe is changed.
Tip: Indicate with the name of a tile if the tile's timeframe can be changed. For example, naming a tile "Performance during the last week" tells users that this tile always shows data for the last week. Naming a tile just "Performance" indicates to users that changing the dashboard timeframe will change the data.
SQL Query
This uses standard Structured Query Language (SQL).
The SQL tab of the SQL Analytics Editor will show everything from the first dataset, as a simple query:
Select * FROM ticketsYou can edit this query to be something more complex. For example, to find the average difference between two different times you can use DATEDIFF and display this it as 'MTTR':
SELECT AVG(DATEDIFF(HOUR, created_at, updated_at)) AS MTTR FROM ticketsYou can also use SQL to query data from more than one dataset, or combine data with a JOIN, etc.
Click Execute to view the SQL Output at the bottom of the screen.
When you are happy with the tile configuration, click Save.
Visualization
Select the visualization for your tile. 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.
Visualization ConfigurationTable settings
Configuration:
| Rename | Click on the column name in the Configuration panel and type to rename it. |
| Sort order | Click and drag a column name to change their order. |
| Hide/show | Click on the Toggle visibility eye button to hide or show a column. |
| Row Link | Hyperlinks each row in the table to the URL in the selected column. |
| Resizing columns | On the table preview hover between column names and use the handle to change the width. Changes will be saved while in the tile editor or in dashboard edit mode. |
| Swap rows and columns | Transpose the table to show the headings as the left-hand column. Particularly useful for single row tables. |
Filtering, grouping and sorting of the data can be configured in the Shaping section.
Reset - reverts to the default settings.
Scalar settings
Data Mapping:
| Value | Choose the column to be used. The default is auto, where the column is chosen by the visualization. |
Configuration:
| Label | Enter a label, for example Tickets or ms. |
| Show formatted value | This shows a simplified value. Toggle to Off to show the raw value. (On by default). |
Reset - reverts to the default settings.
Line Graph settings
Data Mapping:
| X-axis | Choose which data to show on the x-axis. Auto <column> shows the column which was selected automatically for you, usually a time field for the x-axis. |
| Y-axis | Choose which data to show on the y-axis. Auto <column> shows the column which was selected automatically for you, usually a numerical field for the y-axis. |
| Series | Choose how the stack is split into segments, usually a label or a string. |
| Unit | Select the column that you want to use for the unit label. |
Configuration:
| Y-axis range | Auto - graph is fitted to the data automatically Percentage - shows 0-100 Fit to data from zero - shows from 0 to the data maximum Custom - allows you to specify the min and max |
| Data points | This shows where the data points are on the line. Useful to identify missing points, or detail for changing data. |
| Shading | Adds shading below each line. |
| X-axis label | Allows you to override the default and enter a label, for example Date or Time. |
| Y-axis label | Allows you to override the default and enter a label, for example Tickets or ms. |
Bar Chart settings
Data Mapping:
| X-axis | Choose which data to show on the x-axis. Auto <column> shows the column which was selected automatically for you, usually a time field for the x-axis. |
| Y-axis | Choose which data to show on the y-axis. Auto <column> shows the column which was selected automatically for you, usually a numerical field for the y-axis. |
| Unit | Select the column that you want to use for the unit label. |
Configuration:
| Y-axis range | Auto - graph is fitted to the data automatically Percentage - shows 0-100 Fit to data from zero - shows from 0 to the data maximum Custom - allows you to specify the min and max |
| X-axis label | Allows you to override the default and enter a label, for example Date or Time. |
| Y-axis label | Allows you to override the default and enter a label, for example Tickets or ms. |
Blocks settings
Data Mapping:
| State | Select the column that you want to use for the state color of each block. Available options will vary depending on the data stream that you have selected. By default, the State column is automatically selected. |
| Label | Choose the label for the block. |
| Sublabel | Choose the sublabel to be shown beneath the main block label. |
| Link | Select the column that you want to use for the link of each block. Available options will vary depending on the data stream that you have selected. |
Configuration:
| Columns | Set the number of columns the blocks are displayed in. |
| Manual height | Select this to be able to resize the blocks, larger or smaller. |
Reset - reverts to the default settings.
Donut
Data Mapping:
| Value | Choose the column to use for the value for each segment. |
| Label | Choose the label for each segment. |
Stacked Bar settings
Data Mapping:
| X-axis | Choose which data to show on the x-axis. Auto <column> shows the column which was selected automatically for you, usually a time field for the x-axis. |
| Y-axis | Choose which data to show on the y-axis. Auto <column> shows the column which was selected automatically for you, usually a numerical field for the y-axis. |
| Series | Choose how the stack is split into segments, usually a label or a string. |
| Unit | Select the column that you want to use for the unit label. |
Configuration:
| Type | Specify how to group bars, either stacked in a single bar or grouped as separate bars. |
| Mode | Percentage mode displays a series as a percentage of the overall bar, only available for Grouped charts. |
| Layout | Vertical or horizontal. |
| Y-axis range | Auto - graph is fitted to the data automatically Percentage - shows 0-100 Fit to data from zero - shows from 0 to the data maximum Custom - allows you to specify the min and max |
| X-axis label | Allows you to override the default and enter a label, for example Date or Time. |
| Y-axis label | Allows you to override the default and enter a label, for example Tickets or ms. |
| Grid lines | Select whether to include grid lines. |
| Annotation | Display an annotation showing the value for each series. |
Gauge settings
The Gauge visualization shows a single value, often a percentage, in relation to minimum and maximum values. Monitoring can be added so the gauge color changes based on your configured parameters.
Data Mapping:
| Value | Choose which column or count to use as the value for the gauge. Auto <column> shows the column which was selected automatically for you. |
Configuration:
| Range | Specify the min and max of the gauge. |
| Label | Add a label to be shown beneath the gauge. |
| Monitoring | You can configure Monitoring (from the Monitoring tab) and then the colors configured for the conditions will show on the gauge. Check that the Data chosen in the Visualization (e.g. count) and the Value (and Column where applicable) that you are Monitoring (e.g. count) are as intended. |
If you exit out of the SQL Analytics Editor, choosing to revert to using the simple editor for this tile, then you lose your SQL queries and datasets, as only the first dataset is saved.