We use it to stream data from IT devices and process it. We use almost all Azure services, right from Azure AD, Event Hub, Cosmos DB, Azure Stream Analytics, Azure monitoring services, Azure ML Studio, and everything.
We use Azure Stream Analytics to process online event streaming data. It's a versatile solution that can handle various types of streaming data, including deployed streaming data. It also supports JSON format and enables us to analyze IoT data from different organizations within the group.
Our primary use case involves using the app centre to retrieve lifeline data. However, the lifeline is not retrievable from the app centre due to recent changes, so we get it from Azure.
Associate Principal Analyst at a computer software company with 10,001+ employees
Real User
2021-09-24T19:49:20Z
Sep 24, 2021
We were doing some level of stream data processing, so we had some use cases which were related to IoT. We had some IoT devices getting data in from other IoT devices and Azure Streaming Analytics has a special streaming analytics offering for IoT devices. Basically it was used for that.
The company I'm working for is basically one of the biggest companies in the entire Gulf region, including Dubai, Qatar, and Oman. Our core domain is providing logistics. They have different warehouses across the country, and we use it to track the movement of forklifts and people working at the warehouses. The main thing we are focusing on right now is accident avoidance. For example, one forklift is coming through one aisle, and another person is trying to enter the same aisle. We provide a solution that can track the person and forklift in real-time. We're also using it to solve many business problems one by one. Stream Analytics plays a major role in streaming all these huge datasets because we have warehouses spread across the country. It's able to handle millions and millions of events in a few seconds.
Collaboration Consultant at a tech services company with 201-500 employees
Consultant
2020-10-11T08:58:04Z
Oct 11, 2020
I used it once for a project demo to a customer for an IoT solution. In this demo, the data was collected from the sensors, and it was sent to Power BI reports. The collected data was analyzed by using the analytics tools to get some insights. This project was the first project for our company to start the development of IoT solutions. We have only used it for a demo, and we have kept it for demo for other customers. If any customer wants to deploy it, we would use it in production.
We have different kinds of IoT devices placed in different countries including the UK, US, and others. They are configured with our IoT hub and we get the logs from them accordingly. We have these logs connected with the Stream Analytics suites and Microsoft Power BI. Whatever updates and other activity is happening on the devices are streamed into Azure and Power BI so that we can see them. If we find any error messages then we have to check the health of the corresponding IoT devices, databases, and configuration.
Assistant Director - IT Governance Support at a insurance company with 1,001-5,000 employees
Real User
2018-08-22T11:28:00Z
Aug 22, 2018
This solution is connected with our Microsoft license. We use the E3 license, which also includes the software and analytics. We bought it and we are trying to get the best we can from the software. For now, we have some analytics, what's happening, and one of our guys looks at it and prepares reports or maybe requests some additional interventions. It is mostly for analysis so that when something happens we can analyze it and do something about it.
Azure Stream Analytics is a robust real-time analytics service that has been designed for critical business workloads. Users are able to build an end-to-end serverless streaming pipeline in minutes. Utilizing SQL, users are able to go from zero to production with a few clicks, all easily extensible with unique code and automatic machine learning abilities for the most advanced scenarios.
Azure Stream Analytics has the ability to analyze and accurately process exorbitant volumes of...
I use the solution in my company for real-time analytics on IoT data.
We use it to stream data from IT devices and process it. We use almost all Azure services, right from Azure AD, Event Hub, Cosmos DB, Azure Stream Analytics, Azure monitoring services, Azure ML Studio, and everything.
We use Azure Stream Analytics to process online event streaming data. It's a versatile solution that can handle various types of streaming data, including deployed streaming data. It also supports JSON format and enables us to analyze IoT data from different organizations within the group.
We use the solution for real-time data and machine learning features.
The product is used just for the extraction, transforming, and loading of the data to the data warehouse.
Our primary use case involves using the app centre to retrieve lifeline data. However, the lifeline is not retrievable from the app centre due to recent changes, so we get it from Azure.
It's used primarily for data and mining - everything from the telemetry data side of things.
We were doing some level of stream data processing, so we had some use cases which were related to IoT. We had some IoT devices getting data in from other IoT devices and Azure Streaming Analytics has a special streaming analytics offering for IoT devices. Basically it was used for that.
The company I'm working for is basically one of the biggest companies in the entire Gulf region, including Dubai, Qatar, and Oman. Our core domain is providing logistics. They have different warehouses across the country, and we use it to track the movement of forklifts and people working at the warehouses. The main thing we are focusing on right now is accident avoidance. For example, one forklift is coming through one aisle, and another person is trying to enter the same aisle. We provide a solution that can track the person and forklift in real-time. We're also using it to solve many business problems one by one. Stream Analytics plays a major role in streaming all these huge datasets because we have warehouses spread across the country. It's able to handle millions and millions of events in a few seconds.
I used it once for a project demo to a customer for an IoT solution. In this demo, the data was collected from the sensors, and it was sent to Power BI reports. The collected data was analyzed by using the analytics tools to get some insights. This project was the first project for our company to start the development of IoT solutions. We have only used it for a demo, and we have kept it for demo for other customers. If any customer wants to deploy it, we would use it in production.
Our primary use case is mainly to ingest real time data streams into permanent storage places like databases, block storage, etc.
We have different kinds of IoT devices placed in different countries including the UK, US, and others. They are configured with our IoT hub and we get the logs from them accordingly. We have these logs connected with the Stream Analytics suites and Microsoft Power BI. Whatever updates and other activity is happening on the devices are streamed into Azure and Power BI so that we can see them. If we find any error messages then we have to check the health of the corresponding IoT devices, databases, and configuration.
This solution is connected with our Microsoft license. We use the E3 license, which also includes the software and analytics. We bought it and we are trying to get the best we can from the software. For now, we have some analytics, what's happening, and one of our guys looks at it and prepares reports or maybe requests some additional interventions. It is mostly for analysis so that when something happens we can analyze it and do something about it.