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Analytics
premium
Activity
Activity is a single work step inside an Azure Data Factory or Synapse pipeline. In everyday Azure work, teams use it to copy data, run a notebook, call a web endpoint, validate a condition, or control pipeline branching. The useful evidence is activity type, dependencies, retry policy, linked service, inputs, outputs, and run status. Treat
Data Factory
fundamentals
5 commands
Aliases: Data Factory activity, pipeline activity, Synapse pipeline activity
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Analytics
premium
Activity run
Activity run is the execution record for one Azure Data Factory or Synapse pipeline activity during a specific pipeline run. In everyday Azure work, teams use it to pinpoint which step ran, failed, retried, timed out, or produced unexpected output. The useful evidence is run ID, activity name, type, start time, duration, status, error message,
Data Factory monitoring
intermediate
4 commands
Aliases: Data Factory activity run, Synapse activity run, pipeline activity execution
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Analytics
premium
ADX dashboard
ADX dashboard is an Azure Data Explorer dashboard made of KQL-backed tiles and visuals for exploring telemetry or time-series data. In everyday Azure work, teams use it to turn Kusto queries into shared operational views for incidents, trends, business metrics, or engineering reviews. The useful evidence is dashboard owner, data source, base query, tile query,
Azure Data Explorer
intermediate
4 commands
Aliases: Azure Data Explorer dashboard, Kusto dashboard, ADX visualization dashboard
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Analytics
premium
Apache Spark job
An Apache Spark job is a submitted Spark workload, often defined in Azure Synapse as a job definition, that runs batch or streaming code on a Spark pool.
Azure Synapse Analytics
intermediate
3 commands
Aliases: No aliases yet
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Analytics
premium
Auto Loader
Auto Loader is the Azure Databricks feature that watches cloud storage and brings in new files without forcing engineers to rescan everything manually. In plain terms, it is a safer ingestion pattern for folders that keep receiving CSV, JSON, Parquet, images, or other data files. It can process existing files, then continue with new.
Analytics platform
intermediate
4 commands
Aliases: Databricks Auto Loader, cloudFiles, Auto Loader cloud files, Lakeflow Auto Loader
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Analytics
premium
Azure Data Explorer
A fully managed, high-performance analytics service for near-real-time analysis of large telemetry, log, event, and time-series datasets.
Real-time analytics
intermediate
5 commands
Aliases: ADX, Kusto
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Analytics
premium
Azure Databricks
A unified, open analytics platform on Azure for building, deploying, sharing, and maintaining enterprise data, analytics, and AI solutions at scale.
Data engineering and AI
intermediate
5 commands
Aliases: Databricks on Azure
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Analytics
premium
Azure Databricks Unity Catalog
A unified governance layer in Azure Databricks for data and AI assets, including catalogs, schemas, tables, volumes, models, privileges, and lineage.
Data governance
intermediate
5 commands
Aliases: Unity Catalog
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Analytics
premium
Azure integration runtime
Azure integration runtime is the compute infrastructure used by Azure Data Factory and Synapse pipelines to move data, dispatch activities, and connect across network environments.
Data integration compute
intermediate
5 commands
Aliases: Integration Runtime, IR, ADF integration runtime
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Analytics
premium
Azure Synapse Analytics
Azure Synapse Analytics is Microsoft’s integrated analytics service for enterprise data warehousing, big data, data integration, and exploratory analytics.
Synapse Analytics
intermediate
6 commands
Aliases: No aliases yet
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Analytics
premium
Azure-SSIS integration runtime
Azure-SSIS integration runtime is Azure Data Factory or Azure Synapse compute that lets organizations deploy, run, and manage SQL Server Integration Services packages in Azure.
Data Factory
intermediate
5 commands
Aliases: Azure SSIS integration runtime, Azure-SSIS IR
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Analytics
premium
Azure-SSIS IR
Azure-SSIS IR is the Azure integration runtime option that supports deploying, managing, and running SQL Server Integration Services packages in Azure Data Factory or Synapse pipelines.
Data engineering and analytics
intermediate
5 commands
Aliases: Azure SSIS IR, Azure-SSIS integration runtime abbreviation
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Analytics
premium
CETAS
Create External Table As Select, a pattern for writing query results to external storage.
Analytics platform
intermediate
8 commands
Aliases: Create External Table As Select
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Analytics
premium
Change data capture in Data Factory
A Data Factory capability for processing changed data from supported sources.
Data integration
intermediate
10 commands
Aliases: CDC
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Analytics
premium
Copy activity
A analytics platform concept in Data Factory that helps teams move, transform, query, and govern data at scale with clearer ownership, safety, and operational context.
Data Factory
fundamentals
3 commands
Aliases: No aliases yet
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Analytics
premium
Data Factory
Azure’s managed data integration service for creating pipelines that move, transform, schedule, and orchestrate data across cloud, SaaS, and hybrid stores.
Data integration and orchestration
Intermediate
6 commands
Aliases: Data Factory, Data Factory, data factory
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Analytics
top-250-pre130-priority-upgraded
Data Factory activity
Data Factory activity is a unit of work inside an Azure Data Factory pipeline, such as copy, lookup, notebook, stored procedure, web, or data-flow execution in Azure.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory activity, ADF activity, data factory activity
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Analytics
premium
Data Factory connector
A built-in or configured integration capability that lets Data Factory read from or write to a supported data store, SaaS application, or service endpoint.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory connector, ADF connector, data factory connector
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Analytics
premium
Data Factory debug run
An interactive test execution used while authoring a Data Factory pipeline or data flow before publishing or triggering it in production.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory debug run, ADF debug run, data factory debug run
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Analytics
premium
Data Factory expression language
The syntax and function set used in Data Factory to build dynamic values, reference parameters, inspect activity output, and control pipeline behavior.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory expression language, ADF expression language, data factory expression language
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Analytics
premium
Data Factory Git integration
The source-control connection that lets Data Factory authoring use Azure Repos or GitHub branches instead of editing only the live factory mode.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory Git integration, ADF Git integration, data factory git integration
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Analytics
premium
Data Factory global parameter
A factory-level constant that pipelines can reference in expressions and that CI/CD can override per environment.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory global parameter, ADF global parameter, data factory global parameter
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Analytics
premium
Data Factory managed identity
The Microsoft Entra identity assigned to a Data Factory so pipelines and linked services can access Azure resources without embedded passwords.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory managed identity, ADF managed identity, data factory managed identity
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Analytics
premium
Data Factory managed virtual network
A Microsoft-managed network boundary used by Azure Integration Runtime to isolate data integration traffic and connect through managed private endpoints.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory managed virtual network, ADF managed virtual network, data factory managed virtual network
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Analytics
premium
Data Factory monitoring
The operational view of Data Factory pipeline runs, activity runs, trigger history, integration runtime health, metrics, logs, and alerts.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory monitoring, ADF monitoring, data factory monitoring
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Analytics
premium
Data Factory parameter
A read-only value passed into a Data Factory pipeline, dataset, linked service, or data flow so behavior can change at run time.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory parameter, ADF parameter, data factory parameter
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Analytics
premium
Data Factory pipeline
A logical grouping of Data Factory activities that performs a coordinated data movement, transformation, or control-flow process.
Data integration and orchestration
Intermediate
5 commands
Aliases: Data Factory pipeline, ADF pipeline, data factory pipeline
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Analytics
premium
Data Factory private endpoint
A Private Link connection that exposes Data Factory or related data movement targets through a private IP address instead of a public network path.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory private endpoint, ADF private endpoint, data factory private endpoint
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Analytics
premium
Data Factory publish branch
The repository branch where Data Factory stores generated ARM templates after publishing from the collaboration branch.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory publish branch, ADF publish branch, data factory publish branch
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Analytics
premium
Data Factory variable
A mutable pipeline-scoped value that Data Factory activities can set and read during a pipeline run.
Data integration and orchestration
Intermediate
4 commands
Aliases: Data Factory variable, ADF variable, data factory variable
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Analytics
premium
Data flow cluster
The managed Spark compute that Azure Data Factory or Synapse uses to execute a mapping data flow during a debug session or scheduled pipeline run.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow debug
An interactive mapping data flow mode that lets designers preview transformed data and expression results by using an active Spark debug session.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow debug cluster
The live Spark cluster started for a mapping data flow debug session so designers can preview data and run transformation logic interactively.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow debug session
The active design-time session that keeps data flow debug compute available for previewing transformations, expressions, and pipeline debug activity behavior.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow sink
The mapping data flow transformation that writes processed rows to a target dataset, table, file path, or inline destination at the end of a flow branch.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow source
The mapping data flow transformation that reads input rows from a dataset or inline source before downstream transformations reshape the data.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Data flow transformation
A visual operation in a mapping data flow that changes, filters, joins, aggregates, derives, routes, or otherwise reshapes rows between source and sink.
Data Factory
Intermediate
5 commands
Aliases: No aliases yet
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Analytics
verified
Data warehouse
A data warehouse stores curated, structured data for analytics and reporting.
Analytics platform
fundamentals
2 commands
Aliases: No aliases yet
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Analytics
premium
Data warehouse unit
Data warehouse unit is documented by Microsoft as part of the Synapse Analytics area in Azure.
Synapse Analytics
intermediate
5 commands
Aliases: No aliases yet
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Analytics
premium
Databricks access connector
A first-party Azure resource that gives Azure Databricks a managed identity for Unity Catalog storage credentials and other governed service access.
Azure Databricks
intermediate
6 commands
Aliases: Access Connector for Azure Databricks, Azure Databricks access connector, Databricks managed identity connector
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Analytics
premium
Databricks catalog
The top-level Unity Catalog namespace that organizes schemas, tables, views, volumes, models, functions, permissions, lineage, and governed data ownership.
Azure Databricks
fundamentals
6 commands
Aliases: Unity Catalog catalog, Azure Databricks catalog, catalog object
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Analytics
premium
Databricks cluster
A Databricks compute resource that runs notebooks, jobs, libraries, Spark workloads, and data processing tasks using configured runtime, workers, policies, and access controls.
Azure Databricks
fundamentals
6 commands
Aliases: Databricks compute, Azure Databricks compute cluster, classic cluster
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Analytics
premium
Databricks cluster policy
A Databricks governance object that limits which cluster settings users can choose, helping control cost, security, runtime consistency, and workload standards.
Azure Databricks
intermediate
6 commands
Aliases: Databricks compute policy, cluster policy, compute policy
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Analytics
premium
Databricks DBFS
The Databricks file-system abstraction behind dbfs:/ paths, useful for workspace files and legacy mounts but carefully governed alongside Unity Catalog.
Azure Databricks
fundamentals
6 commands
Aliases: DBFS, Databricks File System, dbfs:/
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Analytics
premium
Databricks job
A scheduled or triggered Databricks workflow that runs one or more tasks using configured compute, parameters, retries, notifications, and access controls.
Azure Databricks
fundamentals
7 commands
Aliases: Databricks workflow job, Lakeflow Job, Databricks Jobs
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Analytics
premium
Databricks managed resource group
The Azure resource group created or referenced for Databricks-managed infrastructure that supports a workspace and its classic compute resources.
Azure Databricks
intermediate
6 commands
Aliases: managed resource group, Azure Databricks managed resource group, workspace managed resource group
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Analytics
learning-path-anchor
Databricks metastore
The top-level Unity Catalog container for catalogs, schemas, tables, volumes, models, functions, and governance permissions.
Databricks
intermediate
4 commands
Aliases: Unity Catalog metastore, Databricks Unity Catalog metastore, metastore
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Analytics
learning-path-anchor
Databricks MLflow
The managed MLflow experience in Azure Databricks for experiments, runs, metrics, artifacts, model lineage, and MLOps evidence.
Databricks
fundamentals
4 commands
Aliases: MLflow on Databricks, Databricks experiment tracking, MLflow tracking
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Analytics
learning-path-anchor
Databricks model serving
A managed serving endpoint pattern for exposing Databricks models or AI workloads for online inference with operational controls.
Databricks
intermediate
4 commands
Aliases: Databricks Model Serving, serving endpoint, model serving endpoint
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Analytics
learning-path-anchor
Databricks notebook
A collaborative Azure Databricks document for code, SQL, visualizations, exploration, jobs, and ML workflows attached to compute.
Databricks
fundamentals
4 commands
Aliases: Azure Databricks notebook, Databricks workspace notebook, interactive notebook
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Analytics
learning-path-anchor
Databricks Photon
The native vectorized Azure Databricks engine for accelerating eligible SQL, DataFrame, ETL, and streaming workloads.
Databricks
intermediate
4 commands
Aliases: Photon engine, Photon acceleration, Databricks vectorized engine
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Analytics
learning-path-anchor
Databricks repo
A workspace Git integration, now called Git folders, for versioning notebooks and files used in Databricks development and CI/CD.
Databricks
fundamentals
4 commands
Aliases: Databricks Repos, Databricks Git folder, Azure Databricks Git folders, workspace Git folder
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Analytics
learning-path-anchor
Databricks schema
A Unity Catalog namespace under a catalog that groups tables, views, volumes, models, functions, and permissions.
Databricks
fundamentals
4 commands
Aliases: Unity Catalog schema, Databricks database schema, schema in Unity Catalog
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Analytics
learning-path-anchor
Databricks secret scope
A named Databricks collection of secrets used to store credentials and grant controlled read or manage access to workloads.
Databricks
fundamentals
4 commands
Aliases: Databricks secrets scope, secret scope, Azure Databricks secrets
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Analytics
learning-path-anchor
Databricks SQL warehouse
A Databricks SQL compute resource for interactive queries, dashboards, BI tools, and governed analytics workloads.
Databricks
intermediate
4 commands
Aliases: SQL warehouse, Databricks SQL compute, serverless SQL warehouse
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Analytics
learning-path-anchor
Databricks table
A governed Databricks data object, commonly managed, external, or foreign, queried through Unity Catalog and optimized for analytics.
Databricks
fundamentals
4 commands
Aliases: Unity Catalog table, Delta table in Databricks, Databricks managed table
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Analytics
top-250-pre130-priority-upgraded
Databricks Unity Catalog
Databricks Unity Catalog is the centralized governance layer in Azure Databricks for managing data and AI asset metadata, permissions, lineage, discovery, and workspace access relationships.
Databricks
intermediate
5 commands
Aliases: Unity Catalog in Azure Databricks, Azure Databricks Unity Catalog, governed catalog, Databricks data governance
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Analytics
premium
Databricks workflow
A Databricks workflow is a scheduled or triggered orchestration of tasks in Azure Databricks, commonly managed through Lakeflow Jobs, for running notebooks, SQL, pipelines, scripts, and production data workloads.
Data engineering and analytics
intermediate
5 commands
Aliases: Databricks Jobs workflow, Lakeflow Jobs workflow, Databricks scheduled workflow, Databricks orchestration
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Analytics
premium
Databricks workspace
A Databricks workspace is the Azure resource and collaborative environment where teams create and operate notebooks, jobs, clusters, SQL warehouses, repositories, experiments, and governed data access.
Analytics platform
beginner
5 commands
Aliases: Azure Databricks workspace, Databricks workspace resource, workspace resource, Databricks environment
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Analytics
premium
Databricks workspace Private Link
Databricks workspace Private Link is the Azure Private Link configuration that provides private connectivity paths to Azure Databricks workspace resources and related Databricks services without exposing traffic to the public internet.
Azure Databricks
advanced
5 commands
Aliases: Azure Databricks Private Link, Databricks private endpoint, workspace private endpoint, front-end Private Link
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Analytics
premium
Databricks workspace VNet injection
Databricks workspace VNet injection is the deployment model that places Azure Databricks compute resources into customer-managed virtual network subnets so network security, routing, and private connectivity controls can be applied.
Databricks
advanced
5 commands
Aliases: VNet-injected Databricks workspace, customer-managed VNet workspace, Databricks VNet injection, workspace in customer VNet
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Analytics
premium
Dataset
A dataset is a logical description of data used by analytics or integration services; in Azure Data Factory and Synapse pipelines, it describes the data structure, location, and linked service used by activities.
Data integration
beginner
5 commands
Aliases: data set, logical dataset, pipeline dataset, data reference
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Analytics
premium
Dataset in Data Factory
A dataset in Data Factory is a named JSON definition that describes the data an activity reads or writes, including the linked service, dataset type, path, table, schema, parameters, and annotations.
Data Factory
beginner
5 commands
Aliases: ADF dataset, Azure Data Factory dataset, Data Factory dataset definition, Synapse dataset
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Analytics
premium
Dataset parameter
A dataset parameter is a named value on a Data Factory or Synapse dataset that lets pipelines pass runtime information such as folder, file, schema, table, or partition values into a reusable dataset definition.
Data engineering and analytics
intermediate
5 commands
Aliases: ADF dataset parameter, Data Factory dataset parameter, parameterized dataset, dataset runtime value
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Analytics
top-250-pre130-priority-upgraded
Dedicated SQL pool
Dedicated SQL pool is a provisioned massively parallel processing data warehouse resource in Azure Synapse Analytics used for relational analytical queries at a selected DWU level in Azure.
Analytics platform
fundamentals
7 commands
Aliases: Dedicated SQL pool
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Analytics
premium
Dedicated SQL pool DWU
A data warehouse unit setting that controls performance for a dedicated SQL pool.
Analytics platform
intermediate
4 commands
Aliases: DWU
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Analytics
premium
Dedicated SQL pool pause
Dedicated SQL pool pause stops compute resources for an Azure Synapse dedicated SQL pool so compute charges stop while the database storage remains available and billable.
Analytics platform
intermediate
4 commands
Aliases: pause dedicated SQL pool, Synapse SQL pool pause, pause SQL DW compute
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Analytics
premium
Dedicated SQL pool resume
Dedicated SQL pool resume restarts compute for a paused Azure Synapse dedicated SQL pool so users and workloads can query the warehouse again and compute billing resumes.
Analytics platform
intermediate
4 commands
Aliases: resume dedicated SQL pool, Synapse SQL pool resume, start SQL DW compute
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Analytics
top-250-pre130-priority-upgraded
Delta Lake
Delta Lake is an open-source storage layer that extends Parquet data files with a transaction log to support ACID transactions, scalable metadata, and reliable batch and streaming workloads.
Data lake
intermediate
4 commands
Aliases: Delta format, Delta table storage, lakehouse Delta, Delta Lake
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Analytics
premium
Delta Lake table
A Delta Lake table is a Databricks table stored in Delta format, using data files and a transaction log to support reliable reads, writes, metadata, and table history.
Delta Lake
fundamentals
4 commands
Aliases: Delta table in Delta Lake, Databricks Delta Lake table, Delta format table, lakehouse Delta table
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Analytics
premium
Delta Live Tables
Delta Live Tables is the former name for Lakeflow Spark Declarative Pipelines, a Databricks framework for declarative batch and streaming pipelines using SQL or Python.
Azure Databricks
intermediate
4 commands
Aliases: DLT, Lakeflow Spark Declarative Pipelines, Databricks declarative pipelines, Lakeflow pipelines
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Analytics
premium
Delta table
A Delta table is a table stored in Delta Lake format, combining Parquet data files with a transaction log for reliable batch, streaming, and SQL operations.
Delta Lake
fundamentals
4 commands
Aliases: Databricks Delta table, Delta format table, Delta Lake table, managed Delta table
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Analytics
premium
Delta time travel
Delta time travel is the ability to query or restore earlier versions of a Delta table by using the table history stored in the Delta transaction log.
Delta Lake
intermediate
5 commands
Aliases: Delta Lake time travel, table version query, query previous Delta version, restore Delta table version
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Analytics
premium
Delta transaction log
The Delta transaction log is the file-based record that tracks Delta table commits, metadata, protocol information, and data-file actions for reliable table operations.
Delta Lake
intermediate
5 commands
Aliases: Delta log, _delta_log, Delta Lake log, Delta table log
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Analytics
premium
Distribution column
A distribution column is the column used by a hash-distributed dedicated SQL pool table to assign rows across distributions for parallel query processing.
Dedicated SQL pool
intermediate
4 commands
Aliases: Synapse distribution column, hash distribution column, dedicated SQL pool distribution column, distributed table column
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Analytics
premium
Event trigger
An Event trigger starts an Azure Data Factory or Synapse pipeline in response to supported storage events such as blob creation or deletion. Teams use it to start pipelines automatically when files land, folders change, or storage events indicate that a data integration workflow should run. It is not a scheduled trigger, a tumbling-window trigger, an Event Hubs consumer, or a guarantee that the file is complete and ready for every downstream transformation. In production, confirm factory name, trigger state, storage scope, blob path filters, event type, target pipeline, parameter mapping, managed identity access, publish branch state, and run history.
Data Factory
intermediate
6 commands
Aliases: storage event trigger, Data Factory event trigger, event-based trigger
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Analytics
premium
Execute Pipeline activity
The Execute Pipeline activity lets an Azure Data Factory or Synapse pipeline invoke another pipeline as part of a control-flow workflow. Teams use it to compose reusable parent and child pipelines, pass parameters, and control whether the parent waits for the child pipeline to finish. It is not a copy activity, a trigger, a stored procedure call, or a guarantee that child pipelines share variables or error handling automatically. In production, confirm parent pipeline, child pipeline, parameter map, wait-on-completion setting, activity output, run IDs, failure policy, publish branch, and monitoring evidence for both runs before treating the design as.
Data integration
intermediate
6 commands
Aliases: Execute Pipeline, child pipeline activity, pipeline invocation activity
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Analytics
premium
Expression language
Expression language is the Azure Data Factory and Azure Synapse syntax used to build dynamic values, parameters, conditions, and function calls inside pipeline definitions. Teams use it to make pipeline paths, dates, conditions, parameters, linked-service values, and activity settings change at runtime instead of being hard-coded. It is not general programming code, a SQL dialect, a security boundary, or a guarantee that dynamic values are valid for every dataset and trigger context. In production, confirm expression syntax, parameter names, variable scope, activity output references, trigger metadata, evaluated values, published JSON, debug runs, run IDs, and downstream paths or queries before.
Data Factory
intermediate
6 commands
Aliases: ADF expression language, Data Factory expression language, pipeline expression language, dynamic content
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Analytics
premium
External data source
An External data source is a database object that defines the location and connection information used by SQL engines to access external data. Teams use it to point serverless SQL, dedicated SQL pools, or PolyBase-style queries to data stored outside the database, such as Azure Storage or Data Lake paths. It is not the external table schema, the file format definition, the storage account itself, or proof that the credential can read every file under the path.
Synapse SQL and data virtualization
intermediate
6 commands
Aliases: CREATE EXTERNAL DATA SOURCE, PolyBase external data source, Synapse external data source
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Analytics
premium
External file format
An External file format is a database object that describes the file type, delimiter, compression, and parsing options used to read or write external data. Teams use it to tell SQL engines how to interpret external files such as delimited text, Parquet, ORC, or compressed data before external tables and CETAS jobs use them. It is not the data source location, the external table schema, the actual lake file, or a guarantee that every file in a folder has the same structure.
Synapse SQL and data virtualization
intermediate
6 commands
Aliases: CREATE EXTERNAL FILE FORMAT, PolyBase file format, Synapse external file format
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Analytics
premium
External table
An External table is a SQL table definition whose data is stored outside the database, commonly in Azure Storage or Azure Data Lake Storage. Teams use it to let SQL users query lake files or remote data through familiar table names while the actual data remains in external storage. It is not a managed internal database table, a copy of the data, a storage access policy, or proof that the external files are optimized, fresh, or secure.
Synapse SQL and data virtualization
intermediate
6 commands
Aliases: Synapse external table, SQL external table, PolyBase external table
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Analytics
premium
Fabric capacity
A Fabric capacity is a dedicated pool of compute resources that powers Microsoft Fabric workloads assigned to workspaces. Teams use it to provide shared compute for Fabric workspaces, reports, lakehouses, warehouses, notebooks, pipelines, and real-time workloads under an assigned capacity SKU. It is not a single workspace, a Power BI report, a storage account, a Databricks cluster, or a guarantee that every tenant workload has unlimited performance. In production, confirm capacity name, SKU, region, admin list, assigned workspaces, workload settings, metrics app evidence, throttling, refresh history, pause state, billing owner, and reservation or scaling plan before treating the design as.
Microsoft Fabric
intermediate
6 commands
Aliases: Microsoft Fabric capacity, Fabric F SKU, Fabric compute capacity
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Analytics
premium
ForEach activity
A ForEach activity is an Azure Data Factory or Azure Synapse pipeline control-flow activity that iterates over a collection and executes child activities for each item. Teams use it to run repeatable pipeline steps for files, tables, partitions, API pages, customers, dates, or metadata-driven work items without manually building one activity per item. It is not a mapping data flow transformation, a guarantee of ordered execution when parallelism is enabled, a substitute for idempotent design, or a safe pattern for unlimited fan-out.
Azure Data Factory
intermediate
6 commands
Aliases: ADF ForEach activity, Azure Data Factory ForEach, Synapse ForEach activity, pipeline loop activity
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Analytics
premium
Get Metadata activity
Get Metadata activity is a pipeline step in Azure Data Factory or Synapse that reads information about data instead of copying or transforming the data itself. Teams use it to check whether files exist, list folders, inspect file size or structure, and decide what later pipeline activities should do. In daily Azure work, it shows up when engineers build metadata-driven ingestion, validate landing-zone files, branch with If Condition, loop over child items, or troubleshoot why a copy activity found no input.
Data Factory
beginner
3 commands
Aliases: ADF Get Metadata, Synapse Get Metadata, metadata activity
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Analytics
premium
Global parameter
Global parameter is a Data Factory value defined once at the factory level so multiple pipelines can reference the same environment or configuration setting. Teams use it to avoid hardcoding repeated values such as storage containers, environment names, control-table names, feature flags, or standard paths across many pipelines. In daily Azure work, it shows up when engineers author pipeline expressions, promote factories through CI/CD, override values per environment, debug parameterized datasets, or troubleshoot missing deployment parameters.
Data Factory
beginner
4 commands
Aliases: ADF global parameter, Data Factory global parameter, factory global parameter
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Analytics
premium
Hash distribution
Hash distribution is spreading rows across compute distributions by hashing a chosen distribution column in an Azure Synapse dedicated SQL pool.
Synapse dedicated SQL pool
intermediate
4 commands
Aliases: Synapse hash distribution, dedicated SQL pool hash distribution, Hash distribution, hash-distribution
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Analytics
premium
Hash-distributed table
Hash-distributed table is a dedicated SQL pool table whose rows are assigned to distributions using a hash value calculated from one or more distribution columns.
Synapse dedicated SQL pool
intermediate
4 commands
Aliases: hash distributed table, Synapse HASH table, Hash-distributed table, hash-distributed-table
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Analytics
premium
Hopping window
Hopping window is a Stream Analytics time window that moves forward by a fixed hop while each event can belong to more than one overlapping window.
Stream Analytics
intermediate
4 commands
Aliases: HOPPINGWINDOW, Stream Analytics hopping window, Hopping window, hopping-window
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Analytics
premium
Incremental copy
Incremental copy is the Azure concept that controls how data platforms move changes without reprocessing every source row or file. Teams see it when working with data factory pipelines, copy activity. It is not a full reload, a one-time migration, a backup job, or a blind append into a lake; that distinction matters because bad assumptions create duplicate records, missed changes. Use the term when reviewing ownership, access, monitoring, cost, recovery, or performance. It keeps architects, operators, security reviewers, and support teams focused on the same resource, setting, or behavior.
Azure Data Factory
Intermediate
5 commands
Aliases: incremental load, delta copy, watermark copy, CDC copy, last modified copy
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Analytics
premium
Ingestion mapping
Ingestion mapping controls how streaming or batch data lands in the correct Kusto columns without corrupting schema, losing values, or forcing manual parsing later. Teams see it in azure data explorer tables, kusto databases. It is not a query projection, update policy, table schema alone, Data Factory mapping data flow, or index projection; confusing them can create null columns, failed ingestion. Use the term when reviewing access, monitoring, cost, recovery, or performance. It keeps architects, operators, security reviewers, and support teams focused on the same setting, resource, or behavior.
Azure Data Explorer
Intermediate
5 commands
Aliases: Kusto ingestion mapping, ADX ingestion mapping, table ingestion mapping, JSON ingestion mapping, CSV ingestion mapping
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Analytics
top-250-pre130-priority-upgraded
Integration runtime
Integration runtime controls which compute, region, and network path data integration workloads use when moving data or executing pipeline activities.
Data Factory
intermediate
4 commands
Aliases: ADF integration runtime, Azure integration runtime, self-hosted integration runtime, SSIS integration runtime, IR, Azure Data Factory integration runtime
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Analytics
premium
Kusto cache policy
Kusto cache policy controls which Azure Data Explorer data is kept in hot local cache versus colder storage for faster queries and managed cost.
Azure Data Explorer policies
Advanced
5 commands
Aliases: ADX cache policy, hot cache policy, Kusto hot cache, Azure Data Explorer caching policy
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Analytics
premium
Kusto cluster
Kusto cluster is the Azure Data Explorer compute resource that hosts databases, ingestion, query processing, scale settings, networking, and monitoring for Kusto workloads.
Azure Data Explorer infrastructure
Intermediate
5 commands
Aliases: Azure Data Explorer cluster, ADX cluster, Microsoft.Kusto cluster
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Analytics
premium
Kusto continuous export
Kusto continuous export periodically runs a Kusto query and writes results to an external table destination such as Azure Storage for downstream processing or archiving.
Azure Data Explorer export
Advanced
5 commands
Aliases: ADX continuous export, Kusto export policy, continuous data export
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Analytics
premium
Kusto data connection
Kusto data connection links Azure Data Explorer to event or storage sources such as Event Hubs, Event Grid, or IoT Hub so data can be ingested into a database table.
Azure Data Explorer ingestion
Intermediate
5 commands
Aliases: ADX data connection, Event Hubs data connection, Event Grid data connection, IoT Hub data connection
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Analytics
premium
Kusto database
Kusto database is a logical container inside an Azure Data Explorer cluster that holds tables, functions, policies, permissions, and ingestion/query configuration.
Azure Data Explorer database
Intermediate
5 commands
Aliases: ADX database, Azure Data Explorer database, Kusto DB
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Analytics
premium
Kusto follower database
Kusto follower database is a read-only database attached from another Azure Data Explorer cluster so consumers can query leader data without copying it.
Azure Data Explorer data sharing
Advanced
5 commands
Aliases: ADX follower database, Azure Data Explorer follower database, followed database
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Analytics
premium
Kusto function
Kusto function is a reusable KQL query or query fragment, stored as a database entity or defined ad hoc, that standardizes analytics logic.
Kusto query objects
Intermediate
5 commands
Aliases: Kusto stored function, ADX stored function, KQL function
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Analytics
premium
Kusto ingestion
Kusto ingestion is the process of loading data into Azure Data Explorer tables, where data is validated, mapped, indexed, encoded, and made queryable.
Azure Data Explorer ingestion
Intermediate
5 commands
Aliases: ADX ingestion, Azure Data Explorer ingestion, Kusto data ingestion
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Analytics
premium
Kusto materialized view
Kusto materialized view is a managed aggregation over a source table or another materialized view that keeps a continuously updated result for faster queries.
Kusto query optimization
Advanced
5 commands
Aliases: ADX materialized view, Kusto MV, materialized view in Azure Data Explorer
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