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Energy demand forecasting is an essential component of the energy industry. As an example, the electrical grid relies on an accurate demand forecast to support power generation planning, enable smart strategy on price bidding and to optimize the grid operation. However, building a reliable end to end forecasting solution has always been a challenge. From data collection, storage, model building, and data flow automation each step requires massive resource and time investment. Microsoft Azure provides various services that enable you to address this challenge in a faster and cost efficient way.
In this session, you will learn about how we use Azure Stream Analytics to collect real time data; Azure SQL to store data; Azure Machine Learning to build a forecast model; Azure Data Factory to automate the model and PowerBI to visualize results on a dashboard. At the end of the session, the audience would have the knowledge to create an end to end energy forecasting solution.
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