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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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

Analytics premium Trigger in Data Factory In Azure Data Factory, a trigger determines when a pipeline run starts. Microsoft Learn describes manual, schedule, tumbling window, storage event, and custom event triggers; each carries timing, state, event, or dependency information that Data Factory uses to create pipeline runs. Data integration fundamentals 5 commands Aliases: Data Factory trigger, ADF trigger, Azure Data Factory trigger, pipeline trigger in Data Factory Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

Analytics field-manual-complete Synapse dataset A data structure referenced by Synapse pipelines. Data engineering and analytics intermediate 5 commands Aliases: Azure Synapse dataset, Azure Synapse dataset JSON, Synapse dataset, dataset linked service, integration dataset, pipeline dataset, synapse dataset, synapse-dataset Quick peek Open full term page

Analytics verified Wrangling data flow A wrangling data flow in Azure Data Factory uses Power Query Online to build code-free data preparation logic, then translates the generated Power Query M into Data Flow execution for cloud-scale processing inside pipelines and repeatable scheduled integration workflows at scale. Data Factory fundamentals 5 commands Aliases: ADF wrangling data flow, Power Query data flow, Data Factory data wrangling, Power Query in ADF Quick peek Open full term page

Analytics premium field-manual Mapping data flow A mapping data flow is a visual data transformation flow that runs Spark-based transformations without requiring hand-written Spark code. Teams use it when data teams need to transform, join, clean, or reshape data in pipelines using a design canvas. In plain English, it gives operators a named control for governed transformation logic, reusable pipeline steps, and clearer data movement evidence instead of leaving the decision hidden in a portal setting, script, or deployment file. Treat it as production-ready only when the owner, dependencies, permission boundary, monitoring signal, and rollback evidence are clear. Data Factory intermediate 4 commands Aliases: Mapping data flow, Azure Data Factory, Data Factory, Azure Data Factory and Synapse pipelines, copy activity, wrangling data flow, pipeline activity, ADF mapping data flow, visual data flow Quick peek Open full term page

Analytics command-rich Watermark column In Azure Data Factory incremental copy patterns, a watermark column is a source column, often a last-modified timestamp or increasing key, used to identify rows created or changed since the previous run. The maximum value becomes the next stored watermark. Data engineering and analytics intermediate 5 commands Aliases: incremental copy watermark column, high watermark column, delta load column, LastModified watermark Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

Analytics premium Pipeline In Azure Data Factory or Azure Synapse, a pipeline is a logical grouping of activities that together perform a data workflow. You deploy, schedule, trigger, monitor, and troubleshoot the pipeline as a coordinated unit instead of managing each activity independently. Data integration fundamentals 6 commands Aliases: Data Factory pipeline, Synapse pipeline, data pipeline Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

Monitoring and Observability premium KQL KQL controls how operators search telemetry, detect incidents, investigate performance, build dashboards, create alerts, and summarize operational evidence across Azure services. Teams see it in log analytics workspaces, azure monitor logs. It is not SQL, PromQL, OData filters, ARM template expressions, Azure Data Factory expression language, or application code; confusing them can create missed incidents, expensive queries. 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. Query language Fundamentals 5 commands Aliases: Kusto Query Language, Kusto query, Azure Monitor query language, Sentinel query language Quick peek Open full term page

Analytics premium Pipeline parameter In Azure Data Factory and Azure Synapse pipelines, a pipeline parameter is a run-time input defined at the pipeline level. It cannot be modified during a run, but manual starts, triggers, parent pipelines, and activities can pass values that control paths, settings, filters, or behavior. Data Factory fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

Analytics premium Pipeline run In Azure Data Factory and Azure Synapse, a pipeline run is one execution instance of a pipeline. Each run has a unique run ID, status, timestamps, parameter values, and related activity runs, whether it was started manually, by another pipeline, or by a trigger. Data Factory fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

Analytics premium Pipeline trigger In Azure Data Factory and Azure Synapse, a pipeline trigger defines when and how a pipeline execution starts. Triggers can be scheduled, tumbling-window based, storage-event based, or custom-event based, and they can pass parameter values into the pipeline run they create. Data Factory intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

Analytics premium Pipeline variable In Azure Data Factory and Azure Synapse, a pipeline variable is a value stored within a pipeline run and changed by activities such as Set Variable. Variables are scoped to the pipeline, support String, Bool, and Array types, and are not safe for parallel mutation. Data Factory fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

Analytics premium Tumbling window trigger A tumbling window trigger in Azure Data Factory fires at a recurring interval from a configured start time while retaining state. Microsoft Learn describes it as a fixed, non-overlapping window trigger with one-to-one pipeline association and optional dependencies between windows. Data Factory fundamentals 5 commands Aliases: TumblingWindowTrigger, ADF tumbling window trigger, Data Factory tumbling window trigger, stateful window trigger Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

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 Quick peek Open full term page

Analytics premium Lookup activity A Lookup activity is an Azure Data Factory and Azure Synapse pipeline activity that reads data from a dataset or query, returns a small result to the pipeline, and lets downstream activities use that value for control flow or parameters in governed production environments. Azure Data Factory intermediate 4 commands Aliases: No aliases yet Quick peek Open full term page