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IoT-based scenario

nicolamonaca
New Contributor III

Hi,

We're trying to design a new solution to collect IoT data in real-time on Azure. Could you please suggest me which tools from Azure should we pick along with Databricks?

1 ACCEPTED SOLUTION

Accepted Solutions

lorenz
New Contributor III

To build an IoT data ingestion and processing platform, you can consider using the following Azure tools and services:

Azure IoT Hub: Azure IoT Hub is a fully managed service that enables reliable and secure communication between IoT devices and the cloud. It provides device connectivity, device management, and data ingestion capabilities for your IoT solution.

Azure Event Hubs: Azure Event Hubs is a scalable event processing service that can handle high volumes of streaming data. It can be used for ingesting large amounts of real-time data from IoT devices and acts as an event hub for downstream processing.

Azure Stream Analytics: Azure Stream Analytics is a real-time analytics and complex event processing service. It allows you to process and analyze streaming data from various sources, including IoT devices, using a SQL-like query language.

Azure Functions: Azure Functions is a serverless compute service that enables you to run event-driven code in a scalable and cost-effective manner. You can use Azure Functions to process and transform data as it arrives from IoT devices, triggering functions based on specific events or conditions.

Azure Cosmos DB: Azure Cosmos DB is a globally distributed, multi-model database service that provides high availability and low latency. It can be used to store and query the processed IoT data, allowing you to perform real-time analytics and build responsive applications.

Azure Machine Learning: Azure Machine Learning is a cloud-based service that provides a platform for developing, training, and deploying machine learning models. You can leverage Azure Machine Learning to build predictive and prescriptive analytics models using the IoT data collected from your platform.

Azure Data Lake Storage: Azure Data Lake Storage is a scalable and secure data lake service that allows you to store and analyze large amounts of structured and unstructured data. It can be used as a data repository for your IoT data before processing and analysis.

Azure Monitor: Azure Monitor provides comprehensive monitoring and diagnostics for your Azure resources and applications. It enables you to monitor the performance and health of your IoT data ingestion and processing platform, helping you identify and troubleshoot any issues.

These Azure tools and services can be combined and integrated to create a robust and scalable IoT data ingestion and processing platform. The specific combination and configuration will depend on your specific requirements and use case.

View solution in original post

2 REPLIES 2

nicolamonaca
New Contributor III

Test

lorenz
New Contributor III

To build an IoT data ingestion and processing platform, you can consider using the following Azure tools and services:

Azure IoT Hub: Azure IoT Hub is a fully managed service that enables reliable and secure communication between IoT devices and the cloud. It provides device connectivity, device management, and data ingestion capabilities for your IoT solution.

Azure Event Hubs: Azure Event Hubs is a scalable event processing service that can handle high volumes of streaming data. It can be used for ingesting large amounts of real-time data from IoT devices and acts as an event hub for downstream processing.

Azure Stream Analytics: Azure Stream Analytics is a real-time analytics and complex event processing service. It allows you to process and analyze streaming data from various sources, including IoT devices, using a SQL-like query language.

Azure Functions: Azure Functions is a serverless compute service that enables you to run event-driven code in a scalable and cost-effective manner. You can use Azure Functions to process and transform data as it arrives from IoT devices, triggering functions based on specific events or conditions.

Azure Cosmos DB: Azure Cosmos DB is a globally distributed, multi-model database service that provides high availability and low latency. It can be used to store and query the processed IoT data, allowing you to perform real-time analytics and build responsive applications.

Azure Machine Learning: Azure Machine Learning is a cloud-based service that provides a platform for developing, training, and deploying machine learning models. You can leverage Azure Machine Learning to build predictive and prescriptive analytics models using the IoT data collected from your platform.

Azure Data Lake Storage: Azure Data Lake Storage is a scalable and secure data lake service that allows you to store and analyze large amounts of structured and unstructured data. It can be used as a data repository for your IoT data before processing and analysis.

Azure Monitor: Azure Monitor provides comprehensive monitoring and diagnostics for your Azure resources and applications. It enables you to monitor the performance and health of your IoT data ingestion and processing platform, helping you identify and troubleshoot any issues.

These Azure tools and services can be combined and integrated to create a robust and scalable IoT data ingestion and processing platform. The specific combination and configuration will depend on your specific requirements and use case.

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