The template is equipped with unique Azure icons organized into categories, or Stencils, which each represent a specific function. This arrangement makes it easier for users to access and utilize the appropriate icons for each step in the demand forecasting process.
When to use Azure Demand Forecasting Template
The Azure Demand Forecasting Template is ideal for scenarios where accurate demand predictions are essential. Examples include retail inventory forecasting, hospital visit predictions, and power consumption estimates. By leveraging various Azure services, the template provides a comprehensive framework for actionable insights:
- Event Hubs gathers real-time consumption data.
- Stream Analytics aggregates streaming data and makes it accessible for visualization.
- Azure SQL Database stores and processes the consumption data for analysis.
- Machine Learning applies predictive models to generate the forecast.
- Power BI displays real-time consumption and forecast results in a user-friendly format.
- Data Factory manages and schedules the data flow to ensure a seamless forecasting process.
This template can be applied across different industries to optimize resource allocation and improve decision-making with timely, accurate demand forecasts.
How-To Section: Azure Demand Forecasting Stencils
When implementing the Azure Demand Forecasting Template, various stencils represent specific Azure services. Here's what each stencil does:
- Azure Event Hubs: This stencil represents the service responsible for collecting real-time data. Event Hubs captures large amounts of data from sources like IoT devices, applications, and websites, serving as the entry point for data into the forecasting process.
- Azure Stream Analytics: This stencil is used for processing streaming data in real time. It aggregates and analyzes the data collected by Event Hubs, allowing you to quickly transform and direct it to other Azure services for further processing.
- Azure SQL Database: Represented by this stencil, the SQL Database serves as a storage layer, capturing and organizing data for forecasting. It allows for data transformations, making it easier to prepare data for machine learning models.
- Azure Machine Learning: This stencil represents Azure’s AI and machine learning capabilities. Here, data from the SQL Database is used to build, train, and execute forecasting models, generating predictive insights based on historical and real-time data.
- Power BI: This stencil provides visualization. Power BI connects to data from Azure services, such as Stream Analytics and SQL Database, to create dashboards and reports. This lets you view real-time and forecasted data through interactive visuals, enabling better decision-making.
By combining these stencils, you can create a robust demand forecasting system that accurately predicts consumption, informs resource allocation, and helps manage costs efficiently.
