@kapa.ai how does elementary generate its reports ?

Elementary generates its reports through a two-part process involving the dbt package and the Elementary CLI: 1. Data Collection (dbt Package) When you run

dbt run --select elementary

,

dbt test

, or

dbt build

, the Elementary dbt package collects and stores data in your data warehouse under a dedicated schema (e.g., your_schema`_elementary`). This includes: • dbt test results (stored in

elementary_test_results

) • dbt artifacts such as

dbt_invocations

,

dbt_run_results

,

dbt_models

,

dbt_tests

,

dbt_sources

, and

dbt_exposures

• Anomaly detection results from Elementary tests [Elementary in production] 2. Report Generation (Elementary CLI) The Elementary CLI (

edr

) uses its own internal dbt project to read from the Elementary schema and generate the report. When you run:

edr report

The CLI connects to your data warehouse using the

elementary

profile defined in your

profiles.yml

, reads from the Elementary tables, and generates a self-contained HTML report file. [Generate observability report] The CLI profile only needs read access to the Elementary schema, while the dbt package itself needs read/write access. [Slack discussion] Filtering Reports by Invocation You can also filter the report to a specific dbt run:

edr report --select last_invocation
edr report --select "invocation_time:2022-12-25 10:10:35"
edr report --select invocation_id:XXXXXXXXXXXXX

[Quickstart report] Sharing Reports Once generated, the report can be shared via: • Slack, Amazon S3, or Google Cloud Storage (GCS) using the

edr send-report

command [CLI commands] 👍 0 button 👎 0 button ℹ️ Tip: Mention @elementary.ai in the thread for follow-ups or DM the app for 1-to-1 help.

How do u share using slack ?

Here's how to install the Elementary CLI: 1. Install the Python Package First, install the base CLI package:

pip install elementary-data

Then install the adapter for your specific data warehouse (run only the one you need):

pip install 'elementary-data[snowflake]'
pip install 'elementary-data[bigquery]'
pip install 'elementary-data[redshift]'
pip install 'elementary-data[databricks]'
pip install 'elementary-data[athena]'
pip install 'elementary-data[trino]'
pip install 'elementary-data[clickhouse]'
pip install 'elementary-data[duckdb]'
pip install 'elementary-data[dremio]'
pip install 'elementary-data[spark]'
pip install 'elementary-data[vertica]'
# Postgres doesn't require this step

[Install Elementary CLI] 2. Validate the Installation

edr --help

If you get

command not found: edr

, check the troubleshooting guide. [Quickstart CLI] 3. Configure the Elementary Profile The CLI needs a

profiles.yml

file with an

elementary

profile to connect to your data warehouse. The easiest way to generate it is to run this command inside your dbt project:

dbt run-operation elementary.generate_elementary_cli_profile

Copy the output, fill in any missing credentials, and add it to

~/.dbt/profiles.yml

. Here's an example for Snowflake:

elementary:
  outputs:
    default:
      type: snowflake
      account: [account id]
      user: [username]
      role: [user role]
      private_key_path: [path/to/private.key]
      private_key_passphrase: [passphrase for the private key, if key is encrypted]
      database: [database name]
      warehouse: [warehouse name]
      schema: [schema name]_elementary
      threads: 4
  target: default

[Configuring the Elementary Profile] > Note: Make sure you have already installed the Elementary dbt package and run

dbt run --select elementary

before using the CLI. [Quickstart CLI] 👍 0 button 👎 0 button ℹ️ Tip: Mention @elementary.ai in the thread for follow-ups or DM the app for 1-to-1 help.