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Databricks Workspace Overview

Workspace Homepage

The Workspace homepage offers streamlined onboarding with tiles such as Get started, Recents, and Popular. These provide shortcuts to common actions like notebook creation, file uploads, query editing, and viewing frequently used assets. Displayed content varies based on workspace entitlements. (Microsoft Learn)

The collapsible sidebar leads to core platform sections: Workspace, Recents, Catalog, Jobs & Pipelines, Compute, Marketplace, and persona-based tabs (SQL, Data Engineering, Machine Learning). Features requiring additional entitlements are marked with a lock icon. (Microsoft Learn) The + New menu enables creation of workspace objects (notebooks, jobs, dashboards, alerts, repos) and compute resources. (Microsoft Learn)

Workspace Browser and Object Management

The unified browser supports nested folder structures and drag‑and‑drop placement of notebooks, libraries, experiments, dashboards, files, and alerts. Git folders are integrated alongside workspace folders. You can manage permissions, share folders, and reposition objects using context menus. Full filenames (including extensions) must be unique within a folder. (docs.databricks.com)

  • Recents displays your accessed objects across workloads: notebooks, queries, dashboards, experiments, alerts, and Unity Catalog resources.
  • Popular highlights organization-wide high-interaction assets over the past 30 days. (Microsoft Learn)

Catalog Tab (Unity Catalog Integration)

The Catalog UI enables governance and discovery of data assets across workspaces:

  • It lists catalogs, schemas (formerly databases), tables, views, ML models, and volumes.
  • Supports centralized access policies and lineage tracking. (docs.databricks.com, campus.datacamp.com)

Jobs & Pipelines (Workflows) Tab

Under this tab, you manage job orchestration and pipelines:

  • Create scheduled jobs and Lakeflow pipelines.
  • Define task dependencies, manage retries, and monitor job execution logs. (Microsoft Learn, Microsoft Learn)

Compute Tab

Manages compute infrastructure:

  • All-purpose clusters for interactive work.
  • Job clusters for pipeline execution.
  • SQL warehouses for query workloads. Capable of applying fine-grained cluster policies, autoscaling options, and retention limits. Users can pin clusters to preserve configurations beyond 30 days. (campus.datacamp.com, Microsoft Learn)

SQL, Data Engineering, Machine Learning Tabs

  • SQL: SQL editor interface, dashboards, alerting, and query history.
  • Data Engineering: Monitoring Data Ingestion flows, job runs, pipeline diagnostics.
  • Machine Learning: MLflow experiments, feature store, model registry—excluded from Data Engineer Associate exam scope. (Microsoft Learn, Microsoft Learn)

Top Bar Controls

  • Search: Unified search across all workspace objects including notebooks, tables, dashboards, jobs, files, repos, alerts, and experiments. Filters improve discoverability. (Microsoft Learn)
  • Workspace Switcher: Switch between multiple workspace environments within the same account. (Microsoft Learn, docs.databricks.com)
  • User Settings: Access Settings menu for user preferences, token management, admin configurations, and language change options. (Microsoft Learn, docs.databricks.com)
  • Databricks Assistant: Integrated AI assistant offers code generation, query optimization, and documentation suggestions. Verification with documentation is advised. (docs.databricks.com, Microsoft Learn)

Workspace-Level Controls & Security

Admins manage workspace behavior via Settings, including:

  • Storage policies, UI toggles, notebook result storage, third-party integrations, admin permissions, and sensitive feature enablement (e.g., terminal, preview features). (docs.databricks.com)
  • Workspaces now support binding of storage or service credentials and external locations to specific workspaces for isolation use cases. (docs.databricks.com)

Databricks Apps

Workspaces support building full-stack interactive Databricks Apps that integrate Delta Lake, ML models, notebooks, and Unity Catalog assets. These run on managed infrastructure and can be shared within the workspace. (docs.databricks.com)

Workspaces at Account Level

A Databricks deployment is organized into an account containing one or more workspaces. Unity Catalog integration enables unified identity and governance across workspaces. Best practice for enterprises includes isolating dev, staging, production, or sensitive-data environments into separate workspaces while tracking governance centrally. (docs.databricks.com)

Best Practice Tips

  • Use separate environments (Dev / Prod / Staging) to reduce data risk and optimize governance.
  • Employ Git folders and Repos to coordinate versioned collaboration.
  • Use folder-level ACLs to manage permissions.
  • Keep UX clean by separating sandbox vs production assets.
  • Isolate storage and credentials per workspace when sensitive data is involved. (ittechgenie.com)

Certification Alignment – Data Engineer Associate

Relevant areas for study:

  • Workspace browser and folder structure
  • Cluster creation and policy management (Compute)
  • Job orchestration and pipelines (Jobs & Pipelines)
  • SQL querying and dashboard management Familiarity with search, object organization, and entitlement-aware UI behavior is essential.

Summary Table

Area Key Focus
Workspace Browser Manage notebooks, folders, Git repos, permissions
Sidebar & Navigation Workspace, Recents, Catalog, Jobs & Pipelines, Compute, Marketplace
Top Bar Search, workspace switching, settings, AI Assistant
Catalog Unity Catalog governance of data assets and models
Compute Tab Cluster/warehouse creation, policy enforcement, autoscaling
Jobs & Pipelines Pipeline orchestration, job scheduling, failure retries, monitoring
Databricks Apps Built-in app creation & integration
Workspace Security Credentials binding, settings, admin control, content isolation

Databricks Workspace Interface Tour