Phase 5: Comprehensive Glossary
A
Accelerated Shortcut: Shortcut mode in Real-Time Intelligence that caches data in Eventhouse for fast KQL queries.
ACID: Atomicity, Consistency, Isolation, Durability—transaction properties ensuring data integrity.
Autoscale: Automatic adjustment of node count based on workload demand.
C
Capacity: The compute and storage engine behind Fabric workloads.
CTAS: Create Table As Select—T-SQL statement creating a new table from query results.
Column-Level Security (CLS): Restricts access to specific columns for unauthorized users.
D
Data Workflow Settings: Workspace-level configuration controlling Dataflow Gen2 concurrency and compute allocation.
Dataflow Gen2: Low-code ETL tool using Power Query (M) engine.
Delta Lake: Open-source storage layer providing ACID transactions on data lakes.
Deployment Pipeline: Automated content promotion through development stages.
Deployment Rules: Configuration overrides per deployment stage.
Domain: Logical grouping of workspaces for enterprise governance.
Dynamic Allocation: Spark feature adjusting executor count based on workload.
Dynamic Data Masking (DDM): Obscures sensitive data in query results without modifying stored data.
E
Eventstream: Fabric item for real-time event ingestion and routing.
Event Processor: No-code transformation component within eventstreams.
Eventhouse: Fabric item containing KQL databases for real-time analytics.
F
Fail Activity: Pipeline activity that terminates execution with custom error message.
Full Load: Loading pattern that extracts complete dataset every run.
G
Gateway: On-premises data gateway for connecting to local data sources.
Git Integration: Version control for Fabric items using Azure DevOps or GitHub.
I
Incremental Load: Loading pattern that extracts only new or modified records.
K
KQL: Kusto Query Language—query language for real-time analytics.
KQL Database: Fabric item optimized for time-series and streaming data.
L
Lakehouse: Fabric item combining data lake and warehouse capabilities.
L
Lakehouse: Fabric item combining data lake and warehouse capabilities.
Log Analytics Integration: Feature to export Fabric workspace logs to Azure Log Analytics for advanced querying and compliance.
M
Managed Private Endpoint: Private network connection from Fabric to Azure services using Azure Private Link.
Memory-Optimized Nodes: Spark nodes with higher memory ratio for data-intensive operations.
Mirroring: Replication of external data into Fabric (database or metadata).
Monitor Hub: Centralized monitoring interface for all Fabric activities.
N
Native Execution Engine: Fabric's optimized Spark engine (doesn't support UDFs).
O
OneLake: Unified data lake for all Fabric workloads.
OPTIMIZE: Delta Lake command to consolidate small files.
P
Pipeline: Orchestration item for coordinating data movement and transformation.
Power Query (M): Functional language for data transformation in Dataflows.
R
Real-Time Hub: Monitoring interface for streaming data flows.
Row-Level Security (RLS): Filters rows based on user identity.
S
SCD (Slowly Changing Dimension): Patterns for handling dimension changes over time.
Sensitivity Labels: Classification metadata from Microsoft Purview.
Session Tags: Identifiers enabling Spark session reuse across activities.
Shortcut: Virtual pointer to external data without copying.
Spark Structured Streaming: Spark API for processing streaming data.
Starter Pool: Pre-warmed Spark cluster for fast session start.
Subdomain: Child grouping within a domain for finer governance.
T
TRY/CATCH: T-SQL error handling construct.
Trusted Workspace Access: Configuration allowing Fabric workspaces to bypass Azure Storage firewall rules.
Tumbling Window: Fixed, non-overlapping time intervals for aggregation.
V
V-Order: Microsoft's columnar optimization for Parquet files.
W
Watermark: Tracking value for incremental load progress.
Windowing Functions: Functions that divide streams into finite chunks for aggregation.
Workspace: Container for Fabric items with defined access roles.
Workspace Logging: Export of Fabric activity logs to Azure Log Analytics for compliance and advanced monitoring.