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data-explorer/kusto/functions-library/graph-blast-radius-fl.md

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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph operators](../query/graph-function.md)
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* [Graph Scenarios](../query/graph-scenarios.md)
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* [Graph operators](../query/graph-operators.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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* [graph-path-discovery-fl()](graph-path-discovery-fl.md)

data-explorer/kusto/functions-library/graph-exposure-perimeter-fl.md

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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph operators](../query/graph-function.md)
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* [Graph function](../query/graph-function.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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* [graph-path-discovery-fl()](graph-path-discovery-fl.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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* [graph-path-discovery-fl()](graph-path-discovery-fl.md)
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:::moniker-end

data-explorer/kusto/functions-library/graph-node-centrality-fl.md

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The function `graph_node_centrality_fl()` can be used in the cybersecurity domain to discover important nodes, such as well connected tokens or users, over data modeled as a graph. Various available centrality metrics provide a better understanding of node's posture and allow you to act accordingly. For example, by prioritizing related signals, hardening the node or disrupting unnecessary connections.
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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph function](../query/graph-function.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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* [graph-path-discovery-fl()](graph-path-discovery-fl.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel "
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph operators](../query/graph-function.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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* [graph-path-discovery-fl()](graph-path-discovery-fl.md)
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:::moniker-end

data-explorer/kusto/functions-library/graph-path-discovery-fl.md

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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph function](../query/graph-function.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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* [Functions library](functions-library.md)
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* [Graph semantics overview](../query/graph-semantics-overview.md)
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* [Graph scenarios](../query/graph-scenarios.md)
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* [Best practices](../query/graph-best-practices.md)
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:::moniker-end

data-explorer/kusto/management/graph/graph-model-drop.md

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description: Learn how to delete an existing graph model and all its versions using the .drop graph_model command.
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ms.reviewer: herauch
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ms.topic: reference
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ms.date: 05/28/2025
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---
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# .drop graph_model (preview)
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## Notes
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- The `.drop graph_model` command permanently deletes the graph model and all its versions. This operation cannot be undone.
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- The `.drop graph_model` command permanently deletes the graph model and all its versions. This operation can't be undone.
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- This command also deletes all snapshots associated with the graph model.
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- Dropping a graph model doesn't affect the source data that was used to create it.
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## Next steps
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## Related content
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- [Graph model overview](graph-model-overview.md)
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- [.create-or-alter graph_model](graph-model-create-or-alter.md)

data-explorer/kusto/query/graph-best-practices.md

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This dynamic labeling approach provides exceptional flexibility when modeling graphs with numerous node and edge types, eliminating the need to modify your schema each time a new entity type appears in your data. By decoupling the logical model from the physical implementation, your graph can continuously evolve to represent new relationships without requiring structural changes to the underlying schema.
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## Multi-tenant partitioning strategies for large-scale ISV scenarios
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## Multitenant partitioning strategies for large-scale ISV scenarios
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In large organizations, particularly ISV scenarios, graphs can consist of multiple billions of nodes and edges. This scale presents unique challenges that require strategic partitioning approaches to maintain performance while managing costs and complexity.
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### Understanding the challenge
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Large-scale multi-tenant environments often exhibit the following characteristics:
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Large-scale multitenant environments often exhibit the following characteristics:
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- **Billions of nodes and edges** - Enterprise-scale graphs that exceed traditional graph database capabilities
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- **Tenant size distribution** - Typically follows a power law where 99.9% of tenants have small to medium graphs, while 0.1% have massive graphs
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- **Temporal partitioning** - Separate by time periods for historical analysis
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- **Functional partitioning** - Split by business domain or application area
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**Example: Multi-tenant organizational structure**
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**Example: Multitenant organizational structure**
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```kusto
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// Partition employees and reports by tenant
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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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- [Graph semantics overview](graph-semantics-overview.md)
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- [Common scenarios for using graph semantics](graph-scenarios.md)
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- [Graph function](graph-function.md)
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- [make-graph operator](make-graph-operator.md)
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- [Graph models overview](../management/graph/graph-model-overview.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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- [Graph semantics overview](graph-semantics-overview.md)
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- [Common scenarios for using graph semantics](graph-scenarios.md)
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- [make-graph operator](make-graph-operator.md)
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:::moniker-end

data-explorer/kusto/query/graph-function.md

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description: Learn how to use the graph function to reference a persisted graph entity for querying.
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# graph function (preview)
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>[!INCLUDE [applies](../includes/applies-to-version/applies.md)] [!INCLUDE [fabric](../includes/applies-to-version/fabric.md)] [!INCLUDE [azure-data-explorer](../includes/applies-to-version/azure-data-explorer.md)] [!INCLUDE [monitor](../includes/applies-to-version/monitor.md)] [!INCLUDE [sentinel](../includes/applies-to-version/sentinel.md)]
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>[!INCLUDE [applies](../includes/applies-to-version/applies.md)] [!INCLUDE [fabric](../includes/applies-to-version/fabric.md)] [!INCLUDE [azure-data-explorer](../includes/applies-to-version/azure-data-explorer.md)]
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> [!NOTE]
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> This feature is currently in public preview. Functionality and syntax are subject to change before General Availability.

data-explorer/kusto/query/graph-scenarios.md

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description: Learn about common scenarios for using Kusto Query Language (KQL) graph semantics.
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# Customer intent: As a data analyst, I want to learn about common scenarios for using Kusto Query Language (KQL) graph semantics.
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Combining graph analysis with time-series analytics creates a powerful framework for detecting temporal anomalies while understanding their impact across interconnected systems. This integration delivers significant value for security analytics, IoT monitoring, and operational intelligence.
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:::image type="content" source="media/graphs/Time-series-graph-analytics.png" alt-text="Example image of a workflow diagram using time series and graph analytics.":::
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:::image type="content" source="media/graphs/time-series-graph-analytics.png" alt-text="Example workflow diagram using time series and graph analytics.":::
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### Temporal anomaly detection with context
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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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- [Graph semantics overview](graph-semantics-overview.md)
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- [Best practices for KQL graph semantics](graph-best-practices.md)
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- [Graph function](graph-function.md)
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- [make-graph operator](make-graph-operator.md)
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- [Azure Kusto Graph Samples on GitHub](https://github.com/Azure/azure-kusto-graph-samples)
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- [Advanced KQL graph capabilities for security analysis](https://github.com/Azure/azure-kusto-graph-samples/blob/main/graph%20of%20graph/advanced-kql-capabilities.md)
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- [Digital twins with KQL graph semantics](https://github.com/Azure/azure-kusto-graph-samples/tree/main/digital%20twins)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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- [Graph semantics overview](graph-semantics-overview.md)
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- [Best practices for KQL graph semantics](graph-best-practices.md)
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- [make-graph operator](make-graph-operator.md)
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- [Azure Kusto Graph Samples on GitHub](https://github.com/Azure/azure-kusto-graph-samples)
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- [Advanced KQL graph capabilities for security analysis](https://github.com/Azure/azure-kusto-graph-samples/blob/main/graph%20of%20graph/advanced-kql-capabilities.md)
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- [Digital twins with KQL graph semantics](https://github.com/Azure/azure-kusto-graph-samples/tree/main/digital%20twins)
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:::moniker-end

data-explorer/kusto/query/graph-semantics-overview.md

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- Simulate operating conditions before implementing physical infrastructure changes
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This persistent approach proves invaluable for managing complex IoT ecosystems at scale.
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## Graph querying capabilities
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These capabilities support diverse use cases including customer journey analysis, product recommendation systems, IoT networks, digital twins, and knowledge graphs.
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## Choosing the right approach
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The following decision tree helps you select the most appropriate graph creation approach based on your specific requirements and constraints.
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- **Transient graphs** - Always reflect current data state, ideal for real-time analysis
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## Integration with KQL ecosystem
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:::moniker range="microsoft-fabric || azure-data-explorer"
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- [Common scenarios for using KQL graph semantics](graph-scenarios.md)
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- [Best practices for KQL graph semantics](graph-best-practices.md)
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- [Graph operators](make-graph-operator.md)
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- [Graph model overview](../management/graph/graph-model-overview.md)
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- [Graph snapshots overview](../management/graph/graph-snapshot-overview.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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- [Common scenarios for using KQL graph semantics](graph-scenarios.md)
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- [Best practices for KQL graph semantics](graph-best-practices.md)
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- [Graph operators](make-graph-operator.md)
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- [Graph snapshots overview](../management/graph/graph-snapshot-overview.md)
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:::moniker-end

data-explorer/kusto/query/graph-shortest-paths-operator.md

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## Related content
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:::moniker range="microsoft-fabric || azure-data-explorer"
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* [Best practices for graph semantics](graph-best-practices.md)
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* [Graph operator](graph-function.md)
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* [make-graph operator](../query/make-graph-operator.md)
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* [Graph function](graph-function.md)
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:::moniker-end
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:::moniker range="azure-monitor || microsoft-sentinel"
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* [Best practices for graph semantics](graph-best-practices.md)
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* [make-graph operator](../query/make-graph-operator.md)
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:::moniker-end

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