Cause And Effect Business Analytics And Data Science
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Cause and Effect Business Analytics and Data Science
Among the most important questions that businesses ask are some very simple ones: If I decide to do something, will it work? And if so, how large are the effects? To answer these predictive questions, and later base decisions on them, we need to establish causal relationships. Establishing and measuring causality can be difficult. This book explains the most useful techniques for discerning causality and illustrates the principles with numerous examples from business. It discusses randomized experiments (aka A/B testing) and techniques such as propensity score matching, synthetic controls, double differences, and instrumental variables. There is a chapter on the powerful AI approach of Directed Acyclic Graphs (aka Bayesian Networks), another on structural equation models, and one on time-series techniques, including Granger causality. At the heart of the book are four chapters on uplift modeling, where the goal is to help firms determine how best to deploy their resources for marketing or other interventions. We start by modeling uplift, discuss the test-and-learn process, and provide an overview of the prescriptive analytics of uplift. The book is written in an accessible style and will be of interest to data analysts and strategists in business, to students and instructors of business and analytics who have a solid foundation in statistics, and to data scientists who recognize the need to take seriously the need for causality as an essential input into effective decision-making.
Big Data MBA
Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.
Data Science and Analytics
Author: Dr.Venkateswara Rao Gera
language: en
Publisher: Leilani Katie Publication
Release Date: 2024-09-07
Dr.Venkateswara Rao Gera, Professor, Department of Computer Science and Engineering, Kallam Haranadhareddy Institute of Technology, NH-16, Chowdavaram, Guntur, (D.T), Andhra Pradesh, India. Dr.Padamata Ramesh Babu, Associate Professor, Department of Computer Science and Engineering – Data Science, Bapatla Engineering College, Bapatla (D.T), Andhra Pradesh, India. Dr.Kalyankumar Dasari, Associate Professor & Head, Department of Computer Science and Engineering - Cyber Security, Chalapathi Institute of Technology, A.R.Nagar, Mothadaka, Guntur (D.T), Andhra Pradesh, India. Dr.Shaik Mohammed Jany, Associate Professor, Department of Information Technology and CSE (AI), Narasaraopeta Engineering College, Narasaraopeta, Palnadu (D.T), Andhra Pradesh, India.