Energy Demand Forecast Template with SQL Server R Services

This template demonstrates how to use [SQL Server R Services](https://msdn.microsoft.com/en-us/library/mt674876.aspx) to build an end-to-end, on-prem solution for electricity demand forecasting. For a cloud-based solution using Cortana Intelligence Suite (CIS), please see [CIS Solution Template: Demand Forecasting for Energy](https://gallery.cortanaanalytics.com/SolutionTemplate/Demand-Forecasting-for-Energy-1).The solution template includes a real time data simulator, feature engineering, model retraining, forecasting, and visualization. In this template with SQL Server R Services, we show two versions of implementation: - **Model Development with Microsoft R Server in R IDE**. Run the code in R IDE (e.g., RStudio, R Tools for Visual Studio) with data in SQL Server, and execute the computation in SQL Server. - **Model Operationalization In SQL**. Deploy the modeling steps to SQL Stored Procedures, which can be run within SQL environment (such as SQL Server Management Studio) or called by applications to make predictions. A powershell script is provided to deploy the template automatically. Below is the directory structure for this template: * **SQLR**: SQL stored procedures for data simulation, data preprocessing, feature engineering, model training and scoring. The stored procedures are run on a SQL server. A PowerShell script is provided to automatically deploy the stored procedures on to a SQL server. * **Data**: Sample demand and temperature data for model training and testing. * **R**: R development code (Microsoft R Server). It runs in R IDE, with computation being done in-database (by setting compute context to SQL Server). See Readme files in GitHub for detailed instructions.