Elementary Cloud Demo Videos

Elementary's open-source dbt package provides anomaly detection through dbt tests and uploads metadata and test results to a dedicated schema in your data warehouse.

Elementary onboarding involves setting up environments, installing the dbt package as an SDK, configuring data warehouse and Elementary schema details, and connecting optional integrations for collaboration and monitoring.

Elementary's automated monitors detect data freshness and volume anomalies by tracking patterns in table updates and metadata from information schemas and query histories, without manual configuration.

Elementary captures and uploads all dbt test failures, enabling users to receive alerts, triage issues directly from the UI, view faulty rows, and analyze failed data.

Elementary's data health scoring system categorizes tests into quality dimensions, enabling users to assess data health and communicate data quality.

Elementary detects event freshness anomalies and automates freshness monitoring. Custom dbt tests can enforce SLAs using templates in Elementary's IDE.

This video explains how Elementary integrates with your code repository to automatically create and configure dbt tests, ensuring that they compile correctly and won't break your pipeline. It demonstrates how Elementary scans YAML files, enriches them with model and validation definitions, and opens a pull request for review. Once merged, the tests, including custom SQL validations, will run through dbt and sync results with the Elementary Cloud Platform. This approach bridges the gap between technical users who prefer working with code and non-technical users who can configure tests through the UI while keeping the code as the single source of truth.

Elementary allows data analysts to configure custom queries directly through an IDE, where they can paste their custom SQL logic. This logic is translated into a dbt singular test and stored in the code repository, ensuring that all custom SQL validations are maintained in source control. This structured approach promotes collaboration, repeatability, and seamless integration with the dbt framework.

Elementary includes a native data catalog, serving as an alternative to dbt docs, enriched with high-level results for each data asset. Users can view column and table descriptions, dependencies, last refresh times, and navigate between upstream and downstream assets. The catalog will soon display health scores per table, providing data analysts an easy way to explore datasets and understand their status. For those using advanced enterprise catalogs like Atlan, Elementary is working on partnerships to integrate with such platforms.

Elementary’s lineage feature allows you to inspect test results and data samples directly from the lineage view. You can trace issues back to upstream tables or columns and determine if problems originate from earlier sources. On the Cloud Platform, column-level lineage tracking lets you see how data propagates from source tables to BI assets, including through transformation layers in tools like Looker and Tableau. This detailed view helps assess whether an issue impacts dashboards or remains isolated within earlier layers, with zoom-in options for focused analysis of specific columns.

In the Elementary Cloud Platform, you can manage alerts by marking them with statuses and assigning them to team members, all of which are visible on the Incidents page. Alerts are grouped into incidents based on the error type, and soon they will also be grouped by lineage and error type for better organization. Once an issue is resolved, you will receive a notification. You can assign, change the status or severity, and manage incidents in bulk to avoid alert fatigue. Elementary integrates with tools like PagerDuty and OpsGenie, and upcoming integrations will allow incidents to be sent directly to ticketing systems like Jira, Linear, and ServiceNow

In the Elementary Cloud Platform, you can manage alert routing by creating custom rules to direct alerts to the appropriate channels. For instance, you can route alerts for marketing data assets to a marketing data channel or send alerts from Salesforce source tables to the Salesforce admin team. Alerts can be filtered based on criteria such as resource type, owner, or tag. You can also specify the severity, such as only sending critical errors to certain channels while ignoring warnings. Once configured, alerts matching these criteria will automatically be sent to the relevant teams for action.

You can use the test screen in Elementary to drill down into different test results. The sidebar allows you to inspect data assets by tags, owners, or the structure of your dbt project. Additionally, a database view will be introduced for less technical users, allowing them to navigate the data in a way that’s more familiar to those used to working in a data warehouse console. This makes it easier to explore and inspect test results across different data assets.

Elementary lets you identify model pipeline bottlenecks. You can track failures, execution times, and performance trends, which helps with cost analysis and optimizing heavy models that consume the most compute resources. This insight is useful for improving data SLAs and identifying optimization candidates. Elementary also provides a test performance dashboard, acting as a command center for monitoring test fail rates and flaky tests. You can investigate changes, tweak configurations, and review execution times for tests running in your environment, which helps manage compute and costs. Automated monitors run on Elementary's backend, so their execution times are not shown.