Monitor and collaborate better with improved alerts and security features in Imply Polaris
We’ve launched several new capabilities to the analytical and visual layer in Imply Polaris over the past few months. In this post, we highlight a few of the key features, specifically alerting and security capabilities, and demonstrate how Imply customers can leverage them for their business needs.
Alerts
Polaris data cubes provide a simple visual interface for intuitive exploration and interaction with data through real-time queries. The dimensions and measures are organized so users can drag, drop and drill down to get the insights they need. However, oftentimes, changes to the values of certain metrics (codified as measures in Polaris data cubes) can have critical business implications and it’s not always possible to immediately detect and act on these changes in a timely manner.
The Polaris Alerts feature allows for an intelligent user defined alerting mechanism on key measures in Polaris data cubes. Alerts can be defined with a simple interface that allows users to define the metrics of interest, set the thresholds of alert criteria, and select the timeframe over which to evaluate the metric as well as how frequently the alert query is to be run. The interface allows users to pick standard time ranges (such as a minute, hour etc.) or use custom time ranges using ISO 8601 codes. The feature is also fully integrated with Polaris’ user management functionality- users who set up alerts can control which users or groups of users can view and edit each alert. Furthermore, alerts can be delivered via email, Slack, or to a custom URL via a webhook. Finally, users with view or edit permissions can silence or re-enable an alert at any time.
Below is an illustration of the alert configuration interface set up on a Polaris data cube built on event data for edits to the Wikipedia website. The filter can be used to restrict the data set being evaluated to a certain dimension value. For instance, the filter can be used to evaluate only edits to the english version of the website. Comparison can be made to a different time period against differences in the measure values relative to the current evaluation period. Finally, criteria can be set up against multiple measures.
To learn more about the mechanics of setting up access controls, delivery mechanisms, check out the documentation for Alerts in Polaris.
Resource Based Access Control
Building Polaris visualizations (data cubes and dashboards) is a collaborative process. Multiple users work through the various needs for their analytics applications before arriving at the final product. In order to ensure only the relevant user groups have access, we’ve added support for Resource Based Access control to the various Polaris visual application resources (data cubes, dashboards and alerts).
This feature allows users to assign specific behaviors or permissions to various groups as well as individual users defined in Polaris user management console. Below is a quick illustration of the interface for assigning permissions. By clicking “Add People”, new users and groups can be added and assigned permissions. To learn more, check out the documentation for data cube access.
Row-Level Access Control
With the new Row-Level Security feature, Imply customers can now restrict access to various users to specific subsets of data depending on their groups. When Polaris visualizations are exposed to external users, a robust integration with the identity service will allow for users to view and analyze data only relevant to them.
Security is paramount for this feature. Filters applied on data cubes will also propagate to downstream resources such as dashboard tiles and alerts. This capability is currently only applicable to Polaris visualization resources. There is scope for future work to enable this on Polaris tables (and SQL queries on them etc.)
To learn more about Row-Level Security, check out the documentation for Access Filters in Polaris.
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