Businesses create, transfer and save massive amounts of data from a number of sources as they make the transition to digital. As this happens, solutions that can take all this data, process it faster, evaluate it to perfection, and act upon complex signals, time-sensitive data points, and events in real-time are proliferating and are becoming more important as the number of data sources continues to grow.
How is the information sourced?
This information can be sourced from various places, such as
- Sensor data from assets such as towers, trucks, plants, IoT Edge Devices, etc.
- Databases that support customer-facing web and mobile apps feed Change data captures information that is sent in real time to a process or system.
- Records from applications and infrastructure, both in the cloud and on-premises
All this data can be processed using Microsoft Azure, which provides a variety of solutions, such as real-time intelligence, to meet the changing demands of contemporary businesses.
What is Real-Time Intelligence?
Real-Time Intelligence, which is a component of Microsoft Fabric, presents a fresh way of thinking about real-time analytics.
Importance of Azure Solutions vs. Real-Time Intelligence
Using Azure to Report
In order to create dashboards and reports from past data, Azure provides a number of services. Some examples are:
- For advanced data analysis, use Azure Analysis Services to build multidimensional data models.
- Power Business Intelligence (BI) tool for making dynamic charts and graphs in the cloud.
Some of the limitations of Azure while handling real-time data are:
- Potentially delaying insights and decision-making because reports are prepared using old data, which adds latency.
- Traditional reports lack the capacity to trigger automatic actions or provide real-time alerts since they are static.
- It can be expensive and complicated to scale up conventional reporting infrastructure to manage massive amounts of real-time data in Azure.
What is the solution to the limitations in Azure?
Real-time intelligence reporting offers the following to get around these limitations of Azure reporting:
- Decisions can be made more quickly and nimbly because of the low latency and insights that are created from real-time data.
- Real-time insight systems can enhance operational efficiency by automatically responding to events as they happen.
- Big data analytics benefit from their scalability, which allows them to manage massive amounts of streaming data.
Azure Services for Processing Data in Real-Time
Some of the tools like Azure Data Explorer, Azure Synapse Analytics, and Azure Event Hubs that come with Managed Azure Services provide a variety of tools for processing data in real-time. These tools enable developers to construct efficient structures for data stream capture, processing, and analysis.
- Azure Event Hubs can scale event ingestion to handle millions of events every second.
- Azure Event Grid, an event-routing solution, makes event-driven systems easier to use.
- Azure Data Explorer helps with data analysis by allowing users to quickly and easily explore and visualize data in real-time.
Azure API Management (APIM) makes accessing and sharing real-time data even more secure. All you need to do is combine Azure API management with your RTI solution for secure and controlled access to real-time data. This will allow developers and apps to fully utilize the data for a variety of business purposes.
How does real-time Intelligence help manage data?
As software as a service, the Real-Time Intelligence platform streamlines the handling of time-sensitive data, making it easier to ingest, process, query, analyze, visualize, monitor, alert, and act upon.
- The no-code capabilities provided by real-time analytics make data visualization and exploration simple.
- Makes data processing and ingestion possible.
- Let users create dynamic reports and dashboards.
- Azure Event Hubs, Azure Stream Analytics, and Azure Data Explorer are some of Microsoft’s proven big data and streaming technologies that it works upon internally.
What sets Azure products apart from Real-Time Intelligence? Let’s see the comparison in the table below:
| Capability | Azure Paas-Based Solutions | Real-Time Intelligence Solutions |
| Integration of services | It depends on integration compatibility of services | One-click integration |
| Developer experience | Suitable for Pro Developers | Suitable for all Business users, pro developers, and citizen developers |
| Low Code: No Code | Limited to use in Azure Stream Analytics transformations and alert creation via Logics Apps and Power Automate. The growth of a professional is necessary for the full execution. | It is possible to achieve end-to-end implementation, beginning with intake and ending with action. |
| Multicloud connectors | Estimation, consumption, and billing model based on service. | Integrates with Confluent Kafka, Amazon Kinesis, and Google Pub/Sub. |
| Assistance with CDC data streams | Debezium and other services must be deployed. | Fully integrated with Azure SQL, Postgresql, and Azure Cosmos DB. |
| Protocol Support | Azure Event Hubs, AMQP, Kafka, and MQTT. | Azure Event Hubs, AMQP, Kafka. |
| Data profiling | Not available | An overview of real-time tables’ data profiling |
| Visual Exploration | Not available | Visually analyze your real-time data with drag-and-drop features. |
| Built-in ML models for Anomaly detection and forecasting models | Need pro development to access advanced capabilities | Available |
| Visualization (Third party)
|
Grafana, Kibana, Matlab. | Grafana, Kibana, Matlab, Eventhouse.
|
| Taking business actions from insights | Needs Azure Logic Apps or Power Automate or Azure Functions, Azure Monitor alerts. | Integrating with Power BI Semantic Models, Event stream, and KQL queries, this is available in Fabric through the use of Reflex items in Data Activator.
|
| Reactive system events | Not Available | Built-in events published through Real-Time Hub. |
| Real-time Semantic Models | Not available | Not available |
| Built in AI | Not available | Not available |
| Notification destinations | Service connector portfolio dependent | Microsoft Teams, Microsoft Outlook, and Power Automate connectors. |
Conclusion
Real time intelligence has changed the way business analytics are done and adopting Real-Time intelligence will definitely be a deciding factor in the success of businesses. Real-time intelligence enables businesses to draw important insights, boost operational efficiency, and drive innovation. Businesses can maximize the benefits of real-time data analytics with Real-Time intelligence, as it helps organizations stay ahead by providing a unified platform for data intake, processing, analysis, and action.
