Databricks Intelligence Platform
0%of exam
Data Ingestion + Loading
0%of exam
Data Transformation + Modeling
0%of exam
Lakeflow Jobs
0%of exam
CI/CD
0%of exam
Troubleshooting + Optimization
0%of exam
Governance + Security
0%of exam
Unity CatalogPrivilegesMaskingDelta Sharing
Quick Facts
- Exam
- Data Engineer Associate
- Questions
- 45 scored
- Time
- 90 min
- Fee
- USD 200
- Type
- Multiple choice
- Delivery
- Online/test center
- Aides
- None
- Validity
- 2 years
- Weights
- Not published
- Code
- SQL when possible
Platform Core
- Lakehouse
- Warehouse + lake
- Delta Lake
- ACID table layer
- Unity Catalog
- Governance plane
- Workspace
- Collaborative UI
- Control plane
- Databricks services
- Data plane
- Customer compute
- Photon
- Vectorized engine
- SQL warehouse
- SQL compute
Compute Picker
- Serverless
- Hands-off compute
- SQL warehouse
- BI queries
- All-purpose
- Interactive notebooks
- Job compute
- Per-run compute
- Pool
- Fast startup
- Policy
- Compute guardrails
- Databricks Connect
- Local IDE
- Single node
- Small tests
Ingest CAL
COPY, Auto Loader, Lakeflow Connect
COPY: batchAuto: filesLakeflow: connectors
COPY INTO vs Auto Loader
COPY INTO
- Batch files
- SQL command
- Simple replay
Auto Loader
- Continuous files
- cloudFiles source
- Schema drift
Batch vs stream
Ingestion Picker
- One-time files→COPY INTO(Batch)
- Continuous files→Auto Loader(cloudFiles)
- Enterprise SaaS→Lakeflow Connect(Managed)
- Relational source→JDBC/ODBC(Client)
- API source→REST(Notebook)
- Nested JSON→Auto Loader(Rescue)
- UC file path→Volume(Governed)
Ingestion Methods
- COPY INTO
- Idempotent batch
- Auto Loader
- Cloud file stream
- Lakeflow Connect
- Managed connectors
- JDBC/ODBC
- Database clients
- REST
- API ingestion
- Partner
- External connector
- Local file
- Manual upload
- Volume
- UC file storage
Lakeflow Connect vs JDBC
Lakeflow Connect
- Managed connector
- Enterprise sources
- UC landing
JDBC/ODBC
- Client access
- Custom logic
- Notebook code
Managed vs custom
Auto Loader
- cloudFiles
- Streaming source
- schemaLocation
- Schema tracking
- Checkpoint
- Processed file state
- File events
- Notification mode
- Directory listing
- Listing mode
- addNewColumns
- Fail then evolve
- rescue
- Capture drift
- _rescued_data
- Unexpected fields
Medallion
Bronze -> Silver -> Gold
Bronze: rawSilver: cleanGold: BIQuality rises
View vs Materialized View
View
- Query definition
- Computed on read
- No stored result
Materialized view
- Stored result
- Refreshed data
- Faster reads
Virtual vs stored
Modeling Picker
- Raw landing→Bronze(Preserve)
- Clean entities→Silver(Validate)
- BI metrics→Gold(Aggregate)
- Array column→explode(Flatten)
- Duplicate records→dropDuplicates(Dedup)
- Small dimension→Broadcast join(Avoid shuffle)
Medallion Layers
- Bronze
- Raw landing
- Silver
- Cleaned entities
- Gold
- Business outputs
- Raw columns
- Bronze preserve
- Dedup
- Silver cleanup
- Metrics
- Gold aggregate
- Lineage
- Layer trace
- Quality
- Silver/gold checks
Transform Ops
- Inner join
- Matched rows
- Left join
- Keep left
- Broadcast join
- Small side shipped
- Cross join
- Cartesian product
- Union
- Distinct rows
- Union all
- Keep duplicates
- explode
- Array to rows
- dropDuplicates
- Remove duplicates
- approx_count_distinct
- Fast cardinality
- summary
- Column statistics
Gold Objects
- Table
- Stored Delta data
- View
- Stored query
- Materialized view
- Precomputed query
- Streaming table
- Incremental table
- BI table
- Consumption model
- Metric view
- Governed metrics
- Dashboard
- Visual consumer
- Quality rule
- Reliability check
Jobs DAG
Tasks depend, triggers start, repair reruns
DAG: orderTrigger: startRepair: failed tasks
Scheduled vs Data Trigger
Scheduled
- Clock based
- Fixed cadence
- May run empty
Data trigger
- Data arrival
- Table/file change
- Event aligned
Time vs readiness
Production Picker
- Task dependencies→Lakeflow Jobs(DAG)
- Clock cadence→Scheduled(Time)
- New files→File arrival(Trigger)
- Source tables change→Table update(Trigger)
- Failed task→Repair run(Rerun)
- Dev to prod→DAB(Deploy)
Job Orchestration
- Lakeflow Job
- Pipeline orchestration
- Task
- Work unit
- DAG
- Dependency graph
- Retry
- Failure rerun
- Branching
- Conditional path
- Looping
- Repeated task
- Repair run
- Failed-task rerun
- Run history
- Execution trends
Triggers
- Scheduled
- Time based
- File arrival
- New files
- Table update
- Table changed
- Continuous
- Always running
- Manual
- Run now
- External
- Outside orchestrator
- Dependency
- Upstream task
- Failure rate
- Health signal
Git Folder vs DAB
Git folder
- Branch code
- Commit changes
- Pull request
DAB
- Package assets
- Target config
- Deploy environments
Version vs deploy
DAB Bundle
- DAB
- Declarative deployment
- databricks.yml
- Bundle config
- Target
- Environment config
- Variables
- Reusable settings
- Override
- Target-specific value
- Validate
- Check bundle
- Deploy
- Promote assets
- Git folder
- Workspace repo
Spark UI
Skew, shuffle, spill explain slowness
Skew: unevenShuffle: exchangeSpill: disk
OPTIMIZE vs VACUUM
OPTIMIZE
- Compact files
- Improve reads
- Layout rewrite
VACUUM
- Delete old files
- Reduce storage
- Limits time travel
Speed vs cleanup
Spark Tuning
- Skew
- Uneven partitions
- Shuffle
- Data exchange
- Spill
- Disk overflow
- Partitions
- Parallelism units
- autoBroadcast
- Small join threshold
- Executor memory
- Worker heap
- Driver memory
- Coordinator heap
- Spark UI
- Stage diagnostics
UC Access
Grant base, restrict finer
GRANT: allowDENY: blockMask: valuesFilter: rows
Managed vs External Table
Managed
- UC storage
- UC lifecycle
- Drop deletes data
External
- External location
- Shared files
- Drop keeps data
Owned vs referenced
Governance Picker
- Central governance→Unity Catalog(UC)
- Read access→SELECT(Privilege)
- Hide rows→Row filter(RLS)
- Hide values→Column mask(CLS)
- Tag-driven rules→ABAC(Central)
- External sharing→Delta Sharing(Read-only)
Governance Core
- Catalog
- Top namespace
- Schema
- Database namespace
- Managed table
- UC lifecycle
- External table
- External location
- GRANT
- Add permission
- REVOKE
- Remove permission
- DENY
- Explicit block
- Lineage
- Data flow
- Delta Sharing
- Read-only share
- Federation
- External querying
Row Filter vs Column Mask
Row filter
- Restrict rows
- Tenant isolation
- WHERE-like logic
Column mask
- Transform values
- PII redaction
- Column function
Rows vs values
Security Controls
- Principal
- User/group/SP
- USE CATALOG
- Catalog access
- USE SCHEMA
- Schema access
- SELECT
- Read rows
- MODIFY
- Write rows
- Row filter
- Hide rows
- Column mask
- Transform values
- ABAC
- Tag-based control
- Audit logs
- Access evidence
- System tables
- Operational telemetry
ABAC vs Table Controls
ABAC
- Tag matched
- Central policy
- Owner cannot remove
Table controls
- Per-table setup
- ALTER TABLE
- Owner managed
Central vs local
Common Traps
Current weights
May guide omits weights ≠ Avoid legacy percentages
COPY vs Auto Loader
COPY is batch ≠ Auto Loader streams
Rescue vs evolve
Rescue captures drift ≠ addNewColumns evolves
View vs MV
View stores logic ≠ MV stores results
External drop
Table metadata drops ≠ Files remain
Privilege stack
Need USE parents ≠ SELECT reads table
ABAC access
ABAC restricts only ≠ GRANT still required
VACUUM risk
Cleans old files ≠ Breaks old time travel
Triggers
Schedule uses clock ≠ Data trigger waits
Last Minute
- 1.45 scored; 90 minutes
- 2.May guide: no weights
- 3.SQL when possible
- 4.Auto Loader = cloudFiles
- 5.COPY INTO = batch
- 6.Bronze raw; Silver clean
- 7.Gold = BI outputs
- 8.Jobs are DAG tasks
- 9.DAB deploys assets
- 10.Spark UI finds skew
- 11.UC governs data
- 12.Masks values; filters rows
- 13.ABAC needs base grants
- 14.Delta Sharing is read-only
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