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Databricks Workspace UI Tour — All Menus & Features

Imagine logging into Databricks for the very first time.

You’re the newly hired data engineer at ShopWave, and today is your first day using the platform.
Your lead engineer leans over and says:

“Let’s take a quick tour. Databricks is huge, but you’ll love how everything connects.”

You take a deep breath.
The Workspace loads.
And your journey begins.

🖥️ The Databricks Home Screen

When the Workspace opens, you’ll see:

  • A left navigation sidebar
  • A main content area
  • A top bar with search, settings, profile, and notifications

Let’s explore each part, just like your lead engineer would walk you through it.

📚 Sidebar Overview — The Heart of Navigation

The sidebar is where you’ll find almost everything you need: notebooks, workflows, clusters, data, and more.

Here’s each item explained as a story through ShopWave’s workflow.

1. Workspace​

Your lead engineer clicks Workspace, saying:

“This is where notebooks, folders, and shared projects live.”

Inside Workspace, you’ll find:

  • Your personal folder
  • Team folders
  • Repos (Git-based projects)
  • Shared resources
  • ML and analytics notebooks

ShopWave uses this area to keep projects organized by team → product → workflow.

2. Repos​

Repos connect Databricks to Git providers (GitHub, GitLab, Bitbucket, Azure DevOps).

Your ML teammate explains:

“Every notebook we deploy to production starts here.”

With Repos, teams can:

  • Version notebooks
  • Commit code
  • Run CI/CD
  • Collaborate like software engineers

3. Workspace Browser / Home​

Your “Home” folder is your personal sandbox where you create:

  • Notebooks
  • Experiments
  • Files
  • Scratch work

ShopWave developers use Home as their private playground before publishing work to shared repos.

4. Data​

Your analyst clicks Data and says:

“This is where we explore everything inside the Lakehouse.”

In the Data tab, you can:

  • Browse databases
  • Inspect Delta tables
  • View schemas and sample data
  • Manage catalogs (Unity Catalog)
  • Query data directly

For ShopWave, all sales, orders, inventory, and customer tables are browsable here.

5. Compute​

This is where clusters, SQL warehouses, and compute resources live.

You’ll see:

  • Clusters (for notebooks, Spark jobs, ML)
  • SQL Warehouses (for BI + SQL dashboards)
  • Job compute (for automated pipelines)

Your data engineer says:

“Think of this as your engine room. Without compute, nothing runs.”

6. Workflows​

Workflows = scheduled tasks, ETL pipelines, and automated production jobs.

Inside, you can:

  • Schedule notebooks
  • Run DLT pipelines
  • Trigger jobs based on events
  • View logs and history

ShopWave uses workflows for daily data refresh pipelines.

7. Catalog (Unity Catalog)​

Unity Catalog is Databricks' governance layer.

Here you manage:

  • Users & groups
  • Permissions
  • Table access
  • Audit logs

ShopWave uses this to ensure:

  • Analysts see only what they should
  • Sensitive PII data is protected
  • ML engineers can access feature tables

8. Marketplace​

The Marketplace lets you discover:

  • Public datasets
  • Partner data
  • Analytics-ready data packages

ShopWave uses Marketplace to import:

  • Demographics
  • Weather data
  • Industry benchmarks

9. Dashboards & SQL Editor (in SQL persona view)​

SQL users switch to the SQL UI, which shows:

  • Dashboards
  • Queries
  • Alerts
  • SQL Warehouses

BI teams at ShopWave use this area daily for KPIs, reports, and self-service analytics.

🔍 Top Bar Overview

The top bar contains:

🔎 Global Search​

Find tables, notebooks, dashboards instantly.

🔔 Notifications​

Job failures, run results, cluster alerts.

⚙ Settings​

Manage:

  • Personal tokens
  • Credentials
  • Workspace preferences

👤 Profile​

Sign out, edit profile, manage permissions.

🗂️ What the UI Looks Like When You Work

Let’s walk through a typical ShopWave workflow:

  1. A data engineer opens Workspace → ETL Project
  2. Launches a Notebook
  3. Connects to a Cluster
  4. Reads a Delta table from Data
  5. Writes results into Lakehouse
  6. Schedules the job in Workflows
  7. BI teams view updated KPIs in SQL Dashboards

All workflows start from the same workspace UI, making collaboration fluid.

🧠 Why the Databricks UI Matters

The UI is built for:

  • Beginners → easy to navigate
  • Analysts → SQL-first experience
  • Engineers → notebook + clusters
  • ML teams → experiment tracking & model deployment
  • Admins → governance and monitoring

It brings everyone into one consistent platform.

🏁 Quick Summary

  • Databricks Workspace UI contains all tools for data engineering, analytics, and machine learning.
  • Key sections include Workspace, Repos, Data, Compute, Workflows, Catalog, and Marketplace.
  • The UI is designed for collaboration across engineers, analysts, and data scientists.
  • It supports the full lifecycle: Notebooks → Compute → Pipelines → Dashboards.
  • Understanding the UI is the first step to becoming confident in Databricks.

🚀 Coming Next

👉 Cluster vs SQL Warehouse — Beginner-Friendly Explanation