# From a six-line ticket to embedded analytics on Databricks

> The Dnipro Databricks User Group on building embedded analytics for a production B2B SaaS, and the 5.4x to 6.7x that leaving federated queries bought.

Organised by: Dnipro Databricks User Group
When: 2026-09-26T12:00:00+03:00 to 2026-09-26T13:00:00+03:00 (Europe/Kyiv)
Where: MOST-City, 2 Vulytsya Korolevy Yelyzavety II, Dnipro, 49000, Ukraine
Format: in-person
Speaking: Andrii Taran, Lead Software Engineer, TechFabric
Register: https://usergroups.databricks.com/events/details/databricks-user-groups-dnipro-databricks-user-group-ukraine-presents-from-a-six-line-ticket-to-embedded-analytics-on-databricks/
Canonical: https://www.techfabric.com/events/six-line-ticket-embedded-analytics

---

## About this session

A customer ticket ran to six lines. What it asked for turned into an
architecture spanning Lakehouse Federation, Unity Catalog, AI/BI dashboards,
Delta tables and tenant isolation, running inside a production B2B SaaS
application.

This session is the field report on that. Not the version where every decision
looks deliberate, but what was built, what was measured, what broke, and what
got thrown away and rebuilt.

## What the session covers

- Lakehouse Federation as the way in, getting live application data into
  Databricks without building a pipeline first
- Cutting dashboard query overhead, and consolidating several reports into pages
- Tenant isolation for embedded users, which is the part that has to be right
  before anyone outside the building sees a dashboard
- Moving from federated queries to Delta materialisation, and the 5.4x to 6.7x
  it bought in dashboard performance
- Refresh schedules designed around when the business is actually working,
  rather than around a cron habit
- A real refresh flow for embedded dashboards
- Serverless cold starts, caching and idle cost, measured rather than assumed
- Unity Catalog ownership and the deployment pitfalls that come with it

## Who it's for

Data engineers, software engineers and architects building customer-facing
analytics on Databricks. If you have been asked to put a dashboard inside your
own product and the question of who can see which rows has started to feel
load-bearing, this is the session.