• Introduction to Databricks and Lakehouse architecture
• Databricks account and workspace concepts
• Control plane and compute plane
• Account Admin vs Workspace Admin responsibilities
• Admin Console overview
• Databricks Runtime basics
• Serverless vs Classic Compute
• Administrator roles and responsibilities

• Workspace setup and configuration
• Workspace Admin settings and feature management
• Workspace objects, folders and permissions
• Workspace access management
• DEV / TEST / PROD concepts
• Administrative standards and best practices

• Databricks identity model
• Users, groups and service principals
• Account-level vs workspace-level identities
• Assigning users and groups to workspaces
• Group-based access management and admin roles
• Authentication and SSO concepts
• SCIM / automated provisioning concepts
• Microsoft Entra ID integration overview

• Databricks compute architecture
• All-purpose, Jobs and Serverless compute
• Runtime selection, worker and driver nodes
• Autoscaling and auto termination
• Compute access modes
• Instance pools
• Libraries and dependencies
• Compute policies
• Cluster event logs and common compute issues

• Unity Catalog architecture and metastore concepts
• Catalogs, schemas, tables, views and volumes
• Managed vs external tables
• Storage credentials and external locations
• Object ownership
• GRANT / REVOKE permissions
• Users, groups and privileges
• Data access control and lineage
• Unity Catalog administration best practices

• Databricks security architecture
• Authentication vs authorization
• Role-based access and least privilege
• Personal Access Tokens and OAuth concepts
• Service principal authentication
• Secret management
• Workspace, compute and data permissions
• IP access concepts
• Security troubleshooting

• Databricks monitoring fundamentals
• Admin and compute monitoring
• Cluster event logs and job monitoring
• Query history and audit logs
• Introduction to System Tables
• User activity monitoring
• Failed compute troubleshooting
• Access and permission troubleshooting
• Common production support issues
• Who created this compute?
• Who accessed sensitive data?
• Why did the cluster fail?
•  Which compute is underutilized?
• Which team is consuming the most resources?
• Why did the monthly Databricks cost increase?

• Databricks consumption and DBU concepts
• Compute cost fundamentals
• Usage monitoring by user, team and workload
• Compute tagging
• Compute policies for cost control
• Autoscaling and auto termination optimization
• Identifying idle resources
• Basic cost optimization

• Azure Databricks architecture
• Azure subscriptions, resource groups and workspace deployment
• Managed resource groups
• Azure Storage and ADLS Gen2 integration
• Azure Databricks authentication
• DEV / UAT / PROD architecture
• Azure administration best practices

• Microsoft Entra ID fundamentals
• Users and security groups
• Service principals
• Databricks account identities and identity federation
• Group-based administration
• SSO concepts
• Automated identity provisioning
• Enterprise access-management scenarios

• Enterprise Unity Catalog architecture
• Metastore administration
• Multiple workspace governance and workspace bindings
• Storage credentials and external locations
• Catalog isolation and advanced privileges
• Ownership management
• Service principals with Unity Catalog
• Data lineage and auditing
• Governance design

• ADLS Gen2 architecture
• Storage accounts and containers
• Azure RBAC concepts
• Databricks access to ADLS
• Managed identities and access connectors
• Storage credentials and external locations
• Troubleshooting storage access
• Securing enterprise data

• Azure Databricks networking concepts
• Public vs private connectivity
• VNet and subnet concepts
• Network Security Groups
• Secure cluster connectivity
• Private Link and private endpoint concepts
• IP access lists and firewall considerations
• Network troubleshooting

• Databricks System Tables
• Audit, billing/usage and compute system tables
• Query history and cluster utilization
• User activity and security auditing
• Data-access auditing
• Administrative SQL queries
• Operational dashboards
• Incident investigation

• Databricks billing architecture
• DBU consumption analysis
• Compute utilization and serverless cost considerations
• Cost attribution using tags
• Department/project-level tracking
• Budget monitoring
• Chargeback and showback concepts
• Compute policies and rightsizing
• Idle resource identification
• Enterprise cost-control strategy

• Databricks CLI fundamentals
• Administrative automation
• Service principals for automation
• Infrastructure as Code concepts
• Workspace configuration automation
• Git integrations
• DEV -> UAT -> PROD strategy

• Administrator support model and incident handling
• User login and permission issues
• Compute startup failures
• Library and runtime problems
• Storage-access failures
• Unity Catalog permission problems
• Performance and job failures
• Cost spikes and audit investigations
• Root Cause Analysis
• Production troubleshooting checklist

It is a hands-on course focused on administering, securing, monitoring, governing, and optimizing enterprise Databricks environments.

It is designed for Database Administrators, Azure Administrators, Cloud Engineers, Databricks support professionals, Data Engineers, production support engineers, and IT professionals interested in platform administration.

No. Prior Databricks Administration experience is not required. Basic database/cloud understanding and SQL knowledge are recommended.

You will learn catalogs, schemas, tables, views, volumes, storage credentials, external locations, permissions, ownership, lineage, and governance.

Yes. It covers Azure Databricks architecture, ADLS Gen2, Microsoft Entra ID, Azure networking, identity management, and enterprise Azure administration.

Yes. The curriculum covers system tables, audit and usage monitoring, compute utilization, DBU consumption, tagging, rightsizing, budget monitoring, and cost-control strategies.

Yes. The project covers Workspace → Users & Groups → Compute → Policies → Unity Catalog → Permissions → Monitoring → Cost Control in a practical Databricks environment.

Job roles including Databricks Admin, Azure Databricks Admin, Data Engineer Admin, Platform Architect, and Data Analyst Admin.