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A Practical Introduction to Prescriptive Analytics (with Case Study in R)

Analytics Vidhya

This article was submitted as part of Analytics Vidhya’s Internship Challenge. Introduction “What are the different branches of analytics?” The post A Practical Introduction to Prescriptive Analytics (with Case Study in R) appeared first on Analytics Vidhya. ” Most of us, when we’re.

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How Predictive and Prescriptive Analytics Improve the Call Center Experience

DataKitchen

The post How Predictive and Prescriptive Analytics Improve the Call Center Experience first appeared on DataKitchen.

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Predictive vs. Prescriptive Analytics: What’s the Difference?

Dataiku

When during this process, though, should data executives get either predictive or prescriptive? The bulk of an organization’s data science, machine learning, and AI conquests come down to improving decision-making capabilities.

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Prescriptive Analytics: An Introduction

DataRobot Blog

Where descriptive analytics reveals what has happened in the past, prescriptive analytics delivers insight into optimizing future decisions. As data-driven organizations mature, they will begin to apply prescriptive analytics. by Jen Underwood. Read More.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics. Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes.

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Why prescriptive analytics and decision optimization are crucial

IBM Big Data Hub

Prescriptive analytics helps identify the best course of action that can enable businesses to achieve organizational goals. Although figuring out what you should do is a crucial aspect of business, the value of prescriptive analytics is often missed.

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Prescriptive analytics: The cure for a transforming healthcare industry

IBM Big Data Hub

Prescriptive analytics offers healthcare decision makers the opportunity to influence optimal future outcomes.

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Common Use Cases for Mathematical Optimization

Mathematical optimization is a subset of artificial intelligence and a type of prescriptive analytics. How can this type of prescriptive analytics be applied to lower costs, reduce carbon emissions and build more resilient supply chains?

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Hype Cycle for Supply Chain Strategy, 2020

Read the latest insights on AI, IoT, network design, machine learning, prescriptive analytics and other hot technologies. Gartner’s latest recommendations on tried and true capabilities. Find out what's essential to supply chain excellence. Research insights on new technologies. Vendors you can work with.

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5 Powerful Prescriptive Analytics Examples in Supply Chain

Prescriptive analytics is a type of advanced analytics that optimizes decision-making by providing a recommended action. Supply chain, with its complex planning questions, is typically an area where optimization technology is required. Read about 5 use cases. Supply Chain Network Design. Sales and operations planning (S&OP).

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How to Democratize Data Across Your Organization Using a Semantic Layer

Speaker: speakers from Verizon, Snowflake, Affinity Federal Credit Union, EverQuote, and AtScale

Driving a self-service analytics culture with a semantic layer. Using predictive/prescriptive analytics, given the available data. Avoiding common analytics infrastructure and data architecture challenges. The impact that data literacy programs and using a semantic layer can deliver.