Azure solution architectures

Architectures to help you design and implement secure, highly-available, performant and resilient solutions on Azure.

Demand Forecasting and Price OptimizationPricing is recognized as a pivotal determinant of success in many industries and can be one of the most challenging tasks. Companies often struggle with several aspects of the pricing process, including accurately forecasting the financial impact of potential tactics, taking reasonable consideration of core business constraints, and fairly validating the executed pricing decisions. Expanding product offerings add further computational requirements to make real-time pricing decisions, compounding the difficulty of this already overwhelming task.

Demand Forecasting and Price Optimization

Pricing is recognized as a pivotal determinant of success in many industries and can be one of the most challenging tasks. Companies often struggle with several aspects of the pricing process, including accurately forecasting the financial impact of potential tactics, taking reasonable consideration of core business constraints, and fairly validating the executed pricing decisions. Expanding product offerings add further computational requirements to make real-time pricing decisions, compounding the difficulty of this already overwhelming task.

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Demand ForecastingAccurately forecasting spikes in demand for products and services can give a company a competitive advantage. This solution focuses on demand forecasting within the energy sector.

Demand Forecasting

Accurately forecasting spikes in demand for products and services can give a company a competitive advantage. This solution focuses on demand forecasting within the energy sector.

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Energy Supply OptimizationIn an energy grid, energy consumers are engaged with various types of energy supplying, trading, and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimize the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

Energy Supply Optimization

In an energy grid, energy consumers are engaged with various types of energy supplying, trading, and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimize the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

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利用 SQL Server 最佳化行銷活動此解決方案示範如何利用具備 R Services 的 SQL Server 2016,建置及部署機器學習模型來建議動作,進而將行銷活動目標潛在客戶的購買率提升至最高。

Campaign Optimization with SQL Server

This solution demonstrates how to build and deploy a machine learning model with SQL Server 2016 with R Services to recommend actions to maximize the purchase rate of leads targeted by a campaign.

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