Merge pull request #2526 from cartacioS/sacartac-forecast

Updates to AML Forecasting Solution Architecture

docs/solution-ideas/articles/forecast-energy-power-demand-content.md

@@ -1,11 +1,24 @@
-
+---
+title: Forecast Energy and Power Demand
+titleSuffix: Azure Solution Ideas
+author: cartacios
+ms.date: 3/2/2021
+description: Learn how Microsoft Azure can help accurately forecast spikes in demand for energy products and services.
+ms.custom: acom-architecture, energy demand, power forecast, energy forecast, ai-ml, 'https://azure.microsoft.com/solutions/architecture/forecast-energy-power-demand/'
+ms.service: architecture-center
+ms.category:
+  - ai-machine-learning
+  - integration
+ms.subservice: solution-idea
+social_image_url: /azure/architecture/solution-ideas/articles/media/forecast-energy-power-demand.png
+---
 
 
 [!INCLUDE [header_file](../../../includes/sol-idea-header.md)]
 
 Learn how Microsoft Azure can help accurately forecast spikes in demand for energy products and services to give your company a competitive advantage.
 
-This solution is built on the Azure managed services: [Azure Stream Analytics](https://azure.microsoft.com/services/stream-analytics), [Event Hubs](https://azure.microsoft.com/services/event-hubs), [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning), [Azure SQL Database](https://azure.microsoft.com/services/sql-database), [Data Factory](https://azure.microsoft.com/services/data-factory) and [Power BI](https://powerbi.microsoft.com). These services run in a high-availability environment, patched and supported, allowing you to focus on your solution instead of the environment they run in.
+This solution is built on the Azure managed services: [Azure Stream Analytics](https://azure.microsoft.com/services/stream-analytics), [Event Hubs](https://azure.microsoft.com/services/event-hubs), [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning), [Azure SQL Database](https://azure.microsoft.com/services/sql-database), [Data Factory](https://azure.microsoft.com/services/data-factory), and [Power BI](https://powerbi.microsoft.com). These services run in a high-availability environment, patched and supported, allowing you to focus on your solution instead of the environment they run in.
 
 ## Architecture
 
@@ -14,12 +27,10 @@ This solution is built on the Azure managed services: [Azure Stream Analytics](h
 
 ## Components
 
-* [Azure Stream Analytics](https://azure.microsoft.com/services/stream-analytics): Stream Analytics aggregates energy consumption data in near real-time to write to Power BI.
-* [Event Hubs](https://azure.microsoft.com/services/event-hubs) ingests raw energy consumption data and passes it on to Stream Analytics.
-* [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning): Machine Learning forecasts the energy demand of a particular region given the inputs received.
-* [Azure SQL Database](https://azure.microsoft.com/services/sql-database): SQL Database stores the prediction results received from Azure Machine Learning. These results are then consumed in the Power BI dashboard.
-* [Data Factory](https://azure.microsoft.com/services/data-factory) handles orchestration and scheduling of the hourly model retraining.
-* [Power BI](https://powerbi.microsoft.com) visualizes energy consumption data from Stream Analytics as well as predicted energy demand from SQL Database.
+* [Azure Data Factory](https://azure.microsoft.com/services/data-factory): Handle data manipulation and preparation.
+* [Azure Automated Machine Learning](https://azure.microsoft.com/services/machine-learning/automatedml): Use Azure ML to forecast the energy demand of a particular region.
+* [MLOps](https://azure.microsoft.com/services/machine-learning/mlops): Design, deploy, and manage production model workflows.
+* [Power BI](https://docs.microsoft.com/power-bi/connect-data/service-aml-integrate): Consume model prediction results in Power BI.
 
 ## Next steps
 
@@ -28,4 +39,4 @@ This solution is built on the Azure managed services: [Azure Stream Analytics](h
 * [Learn more about Azure Machine Learning](/azure/machine-learning/overview-what-is-azure-ml)
 * [Learn more about SQL Database](/azure/sql-database)
 * [Learn more about Data Factory](/azure/data-factory/data-factory-introduction)
-* [Learn more about Power BI](https://powerbi.microsoft.com/documentation/powerbi-landing-page)
+* [Learn more about Power BI](https://powerbi.microsoft.com/documentation/powerbi-landing-page)

docs/solution-ideas/articles/forecast-energy-power-demand.yml

@@ -3,9 +3,9 @@ metadata:
   title: Forecast Energy and Power Demand
   titleSuffix: Azure Solution Ideas
   description: Give your company a competitive advantage by using Microsoft Azure to help accurately forecast spikes in demand for energy products and services.
-  author: doodlemania2
+  author: cartacios
   ms.author: pnp
-  ms.date: 12/16/2019
+  ms.date: 3/2/2021
   ms.topic: conceptual
   ms.service: architecture-center
   ms.subservice: solution-idea
@@ -27,12 +27,9 @@ azureCategories:
   - integration
 summary: Give your company a competitive advantage by using Microsoft Azure to help accurately forecast spikes in demand for energy products and services.
 products:
-  - azure-stream-analytics
-  - azure-event-hubs
   - azure-machine-learning
-  - azure-sql-database
   - azure-data-factory
   - power-bi
-thumbnailUrl: /azure/architecture/browse/thumbs/forecast-energy-power-demand.png
+thumbnailUrl: /azure/architecture/browse/thumbs/automl-forecast-energy-demand.png
 content: |
   [!include[](forecast-energy-power-demand-content.md)]