Learn Databricks from the ground up.

One concept, one page. The same explanations reachable three ways: from the product area, from a learning path, and from the certification roadmap.

163
concepts
8
paths
575
resources
Start here
The Data Engineer Associate track

7 exam domains, 45 questions, mapped one by one onto concepts you can read here. It follows the official exam guide, version 2026-05.

Open the roadmap Data Engineering path Graph
New here? Start with
01Architecture of the Data Intelligence Platform02Choosing compute: all-purpose, job cluster, serverless, SQL warehouse03Delta Lake, the lakehouse table format

Learning paths

8 of them, in orderView all
prerequisitesBeginner
SQL & Python Foundations

The SQL and PySpark you need before any other path: the Spark dialect, types, joins, windows, MERGE, and the DataFrame API as it differs from pandas.

15 concepts·4 stages·~25 h
start hereBeginner
Lakehouse Foundations

How the Databricks platform is put together: control plane and compute, Delta Lake as the storage format, Unity Catalog as the governance layer, and the medallion pattern everything else builds on.

9 concepts·4 stages·~20 h
pipelinesIntermediate
Data Engineering

Build production pipelines: ingest with Auto Loader, COPY INTO and Lakeflow Connect, transform with PySpark and SQL, orchestrate with Lakeflow Jobs, and ship it with bundles.

52 concepts·6 stages·~60 h
unity catalogIntermediate
Governance & Security

Unity Catalog end to end: the three-level namespace, managed and external tables, privileges, row filters, column masks and attribute-based policies.

16 concepts·4 stages·~15 h
operationsAdvanced
Platform & Administration

Choose the right compute, read the Spark UI, tune the handful of settings that matter, and diagnose clusters that will not start or run out of memory.

16 concepts·4 stages·~25 h
warehouse & BIBeginner
SQL & Analytics

Query the lakehouse from the SQL editor, model gold tables and views for BI, and understand what a SQL warehouse costs.

30 concepts·3 stages·~30 h

Latest news

All news

No news published yet. News comes from the official release notes, proposed by the agent and approved by a human.

Recently updated

163 concepts
Agent and MCP services as Unity Catalog securablesmodel services made an LLM endpoint a Unity Catalog object. The same idea now covers the two other things an agent is made of:12 Sept 2026Agent Bricks: Knowledge Assistant and Supervisor AgentTwo builders you configure instead of code, both reached from Agents in the workspace sidebar, both producing an agent endpoint you can query from the AI Playground, from an app, or over the API.12 Sept 2026Deploy an agent on Databricks AppsDatabricks documents one way to ship a custom agent: write it as an ordinary Python project, then run that project as a Databricks App. Two pieces are fixed and the rest is yours.12 Sept 2026Agents on DatabricksAn agent is a program that decides what to do. It takes a request, chooses which tools to call and in what order, reads the results, and produces an answer. The model does the choosing; everything else is ordinary software.12 Sept 2026Agent memoryManaged agent memory gives an agent something to remember between conversations. Databricks runs the storage and the isolation; you get a memory store, which is a Unity Catalog securable holding entries.12 Sept 2026
Take it with you

Every concept is a markdown file

The whole site is written in a folder you can open in Obsidian: wikilinks resolve, the graph view works, callouts render. No plugins, nothing to configure.

Open on GitHub Download the vault
  1. 1Download or clone the repository.
  2. 2In Obsidian choose "Open folder as vault".
  3. 3Point it at the content folder. That is the whole setup.

Renamed recently

All renames

Exam guides keep the old names for months. These are the ones that catch people out.

Mosaic AI Gateway → Unity Gateway2026-08-04Genie spaces → Genie Agents2026-07Delta Sharing → OpenSharing2026-06-10Genie → Genie One2026-06-09

In preview

The radar

What Databricks is shipping but has not settled. Worth investigating, not worth betting on.

ABAC DENY policiesAttribute-based policies that deny rather than grant, evaluated against governed tags. BetaDashboard relationshipsA join graph across AI/BI dashboard datasets, resolved at query time, with cross-dataset measures over several fact tables. PreviewRelationship-scoped and cross-dataset filtersA filter that travels across datasets through the relationships defined on the dashboard. Preview

Ending soon

All dates

Runtimes, models and APIs with a date on them. Relevant if you have something in production.

Workspace entitlement inheritance becomes mandatoryThe enforcement date for inherited entitlements, with no opt-out left.in 2 daysThe Supervisor APIThe Beta API for supervisor agents reaches end of life and stops being available.in 18 daysGemini 2.5 Flash and 2.5 ProBoth retire on the same day, Flash from pay-per-token and Pro from provisioned throughput.in 20 days

Resources

575 free
Register agents (agent services)Documentation · DatabricksFreeRegister an external MCP serverDocumentation · DatabricksFreeGovern an MCP serviceDocumentation · DatabricksFreeCreate a data profile using the APIDocumentation · DatabricksFreeData profiling metric tablesDocumentation · DatabricksFreeUse custom metrics with data profilingDocumentation · DatabricksFree