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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

This is what makes the casino industry a great use case for prescriptive analytics technologies and applications. The need for prescriptive analytics. Prescriptive analytics is the area of business analytics (BA) dedicated to finding the best course of action for a given situation.

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3 Things Citizen Data Scientists Need in Predictive Analytics!

Smarten

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Forecasting. Access to Flexible, Intuitive Predictive Modeling. Competitive Changes.

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Prescriptive Analytics – a Winning Bet for Casinos

BizAcuity

This is what makes the casino industry a great use case for prescriptive analytics technologies and applications. The need for prescriptive analytics. Prescriptive analytics is the area of business analytics (BA) dedicated to finding the best course of action for a given situation.

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Automated Sales Forecasting with Predictive Analytics Making AI Real (Part 4)

Jedox

In today’s organizations, the role of financial controlling or FP&A is not only to provide financial insights so business partners can make better decisions, but it is also to lead the way towards a more mature use of analytics technology including predictive analytics for sales forecasting. Making AI Real (Part 2).

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Some examples of data science use cases include: An international bank uses ML-powered credit risk models to deliver faster loans over a mobile app. An AI-based medical assessment platform analyzes medical records to determine a patient’s risk of stroke and predict treatment plan success rates.