Fabric DP-700 flashcards
Fabric DP-700 · Build recall with a focused review session.
33 cards. Read the term and the definition here. The deck at the top of this page is optional.
- OneLake
- The single logical data lake for a tenant, built on ADLS Gen2 with a hierarchical namespace. Every Fabric item stores its data in OneLake under workspace and item folders.
- Fabric workspace roles
- Admin, Member, Contributor, and Viewer. Contributors create and edit items, Viewers are read-only, and only Admins can manage workspace permissions and membership.
- OneLake shortcut
- An object that points to data stored elsewhere, such as ADLS Gen2, Amazon S3, Dataverse, or another OneLake path, without copying it. Reads are served from the source.
- Database mirroring
- Continuous near real-time replication of an external source database into OneLake as Delta tables. Mirrored data is read-only and queryable by Spark, SQL, and Power BI.
- Deployment pipeline
- A Fabric tool that assigns workspaces to stages such as Development, Test, and Production and copies item definitions between them, with rules that override connections and parameters per stage.
- SQL analytics endpoint
- A read-only T-SQL surface created automatically with each lakehouse over its Delta tables. It supports SELECT and metadata queries but not data modification.
- Fabric Warehouse item
- A relational item supporting full T-SQL DML, multi-table transactions, stored procedures, and views, with data persisted in Delta format in OneLake.
- Fabric capacity SKU
- Capacity is purchased in capacity units with SKUs from F2 to F2048. A workspace must be assigned to a capacity before its items can execute.
- Promotion versus certification
- Promotion endorses an item as trustworthy and requires write permission on it. Certification requires approval from a tenant-designated group and marks organization-trusted data.
- Fabric domains
- A governance construct that groups workspaces into business areas, letting administrators delegate workspace assignment and control how data is discovered by users.
- Sensitivity label inheritance
- Microsoft Purview labels applied to a Fabric item are inherited by downstream items that Fabric can trace through lineage, so protection follows the data.
- Copy job
- A Fabric item for no-code bulk and incremental data movement between supported sources and destinations, supporting column mapping and change-based copying.
- Dataflow Gen2
- A Power Query Online-based item that extracts, transforms, and loads data. Output destinations include lakehouse tables, warehouse tables, and KQL databases.
- Eventstream
- A Fabric item that ingests streaming data from Event Hubs, IoT Hub, Kafka, or sample sources and routes it to lakehouse, KQL database, derived streams, or a custom endpoint.
- Medallion architecture
- A layered data design where bronze holds raw ingested data, silver holds cleansed and conformed data, and gold holds business-level aggregates used for reporting.
- Delta transaction log
- An ordered JSON log stored in the _delta_log folder that records every change to a Delta table, enabling ACID transactions, schema enforcement, and time travel.
- OPTIMIZE command
- A Delta operation that compacts many small files into fewer larger ones and can optionally apply Z-ORDER, improving read performance after frequent incremental writes.
- VACUUM default retention
- VACUUM deletes data files no longer referenced by the Delta log. The default retention threshold is seven days unless the retention check is explicitly disabled.
- V-Order
- A write-time Parquet optimization in Fabric that sorts and compresses row groups to accelerate reads, especially Power BI Direct Lake queries. It is enabled by default.
- Watermark incremental load
- A pattern that stores the maximum value of a column such as last-modified timestamp, then copies only rows newer than that watermark on each subsequent run.
- ForEach activity
- A pipeline activity that iterates over an array of items. Its batch count setting controls how many iterations execute in parallel during the run.
- Queued versus streaming ingestion
- Streaming ingestion writes KQL events with low latency but limited throughput; queued ingestion batches data for higher throughput with seconds-to-minutes delay.
- Monitoring hub
- A Fabric portal page listing activity runs, item runs, and refreshes across workspaces with status, duration, and error details, filterable by workspace, item, and time.
- Capacity metrics app
- A Power BI app that reports compute and storage consumption per workspace and item for a Fabric capacity, along with overload, throttling, and autoscale signals.
- Capacity smoothing
- A mechanism that spreads short compute spikes over a 24-hour window so brief peaks above the capacity limit do not immediately cause throttling.
- Capacity bursting
- A behavior that lets a workload temporarily consume more than its provisioned capacity by borrowing against future capacity, with the debt recovered later through smoothing.
- Query insights
- A Fabric Warehouse feature that surfaces the longest-running and most frequent queries with their execution plans and resource usage so they can be tuned.
- Spark Advisor
- Automated guidance surfaced after Fabric notebook runs that flags issues such as partition skew, oversized shuffles, or inefficient joins with suggested remediations.
- Direct Lake fallback
- When a semantic model cannot read Delta tables directly, for example due to unsupported data types or excessive files, it falls back to DirectQuery, which performs more slowly.
- Result set caching
- A warehouse feature that stores query results so identical repeated queries return from cache. It can be enabled or disabled per session with SET RESULTSET_CACHE.
- Statistics in warehouse
- Metadata describing column value distribution that the query optimizer uses to estimate row counts. Missing or stale statistics produce poor execution plans.
- KQL materialized view
- A KQL database object that stores the precomputed result of a summarization query over a source table and is kept current automatically as new data arrives.
- Fabric throttling stages
- Escalating responses to capacity overload: interactive delay first, then interactive rejection, then background rejection, applied once smoothed utilization exceeds capacity limits.