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Authors: Amar Sahay
Chapter from: "Business Analytics: A Data-Driven Decision-Making Approach for Business Volume II"
Published by: Business Expert Press
Originally published in: 2020
Revision date: 28-Nov-2019

Abstract

This chapter is excerpted from 'Business Analytics: A Data-Driven Decision-Making Approach for Business Volume II'. This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA - descriptive, predictive, and prescriptive - along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics - machine learning, neural networks, and Artificial Intelligence. The concluding chapter discusses the current state, job outlook, and certifications in analytics.

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Abstract

This chapter is excerpted from 'Business Analytics: A Data-Driven Decision-Making Approach for Business Volume II'. This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA - descriptive, predictive, and prescriptive - along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics - machine learning, neural networks, and Artificial Intelligence. The concluding chapter discusses the current state, job outlook, and certifications in analytics.

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