There is no inbuilt features to built-in โcommentary workflowโ like your Java app. But you can custom build one. Here are the steps to build one.
1. Use Databricks SQL Dashboards or Lakeview Dashboards for your YoY/QoQ variance analysis.
2. Create a Delta table to store comments, approvals, and metadata. Something like this.This table can be secured with UC for RBAC (who can comment, who can approve).
%sql
CREATE TABLE commentary (
id BIGINT GENERATED ALWAYS AS IDENTITY,
metric STRING,
period STRING,
variance DOUBLE,
comment STRING,
status STRING, -- e.g., 'Pending', 'Approved'
created_by STRING,
created_at TIMESTAMP,
approved_by STRING,
approved_at TIMESTAMP
);
3. Use Databricks SQL to expose the data intersection (metric + period) where variance > threshold.
4. Build a custom UI (React/Next.js or Streamlit on Databricks) that:
--- Lists flagged variances.
---Allows adding comments.
5. In Lakeview Dashboards, you can add a custom URL action:
----Example: https://your-commentary-app?metric={{metric}}&period={{period}}
6. Use Databricks Workflows or Jobs to:
---Trigger alerts when new variances exceed thresholds.
---Send email/Slack notifications for pending approvals.