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Data Science For Business And Decision Making

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Data Science for Business and Decision Making

Data Science for Business and Decision Making Book
Author : Luiz Paulo Fávero,Patrícia Belfiore
Publisher : Academic Press
Release : 2019-04-11
ISBN : 0128112174
Language : En, Es, Fr & De

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Book Description :

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Data Science for Business

Data Science for Business Book
Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Release : 2013-07-27
ISBN : 144937428X
Language : En, Es, Fr & De

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Book Description :

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Real World Data Mining

Real World Data Mining Book
Author : Dursun Delen
Publisher : FT Press
Release : 2014-12-16
ISBN : 0133551113
Language : En, Es, Fr & De

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Book Description :

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.

Business Analytics Data Analysis Decision Making

Business Analytics  Data Analysis   Decision Making Book
Author : S. Christian Albright,Wayne L. Winston
Publisher : Cengage Learning
Release : 2014-02-28
ISBN : 9781133629603
Language : En, Es, Fr & De

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Book Description :

Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 5E! This quantitative methods text provides users with the tools to succeed with a teach-by-example approach, student-friendly writing style, and complete Excel 2013 integration. It is also compatible with Excel 2010 and 2007. Problem sets and cases provide realistic examples to show the relevance of the material. The Companion Website includes: the Palisade DecisionTools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); SolverTable, which allows you to do sensitivity analysis; data and solutions files, PowerPoint slides, and tutorial videos. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Business Analytics

Business Analytics Book
Author : U. Dinesh Kumar
Publisher : Unknown
Release : 2017
ISBN : 9788126568772
Language : En, Es, Fr & De

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Book Description :

Written with the aim of becoming the primary resource for students of business analytics, this book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries.

Getting Started with Business Analytics

Getting Started with Business Analytics Book
Author : David Roi Hardoon,Galit Shmueli
Publisher : CRC Press
Release : 2013-03-26
ISBN : 1439896534
Language : En, Es, Fr & De

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Book Description :

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.

Data Science for Business and Decision Making an Introductory Text for Students and Practitioners

Data Science for Business and Decision Making  an Introductory Text for Students and Practitioners Book
Author : Seyed Ali Fallahchay
Publisher : Arcler Press
Release : 2020-11
ISBN : 9781774076217
Language : En, Es, Fr & De

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Book Description :

This book explores the principles underpinning data science. It considers the how and why of modern data science. The book goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making. Using real life examples, this book explores the possibilities and limitations of an information-based decision making framework.

Data Science and Multiple Criteria Decision Making Approaches in Finance

Data Science and Multiple Criteria Decision Making Approaches in Finance Book
Author : GOEKHAN. DINCER SILAHTAROGLU (HASAN. YUKSEL, SERHAT.)
Publisher : Springer Nature
Release : 2022-01-21
ISBN : 3030741761
Language : En, Es, Fr & De

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Book Description :

This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.

Business Analytics Volume II

Business Analytics  Volume II Book
Author : Amar Sahay
Publisher : Business Expert Press
Release : 2019-11-08
ISBN : 1631574809
Language : En, Es, Fr & De

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Book Description :

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 on 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 on the current state, job outlook, and certifications in analytics.

Analytics and Data Science

Analytics and Data Science Book
Author : Amit V. Deokar,Ashish Gupta,Lakshmi S. Iyer,Mary C. Jones
Publisher : Springer
Release : 2017-10-05
ISBN : 3319580973
Language : En, Es, Fr & De

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Book Description :

This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.

Business Analytics Volume I

Business Analytics  Volume I Book
Author : Amar Sahay
Publisher : Business Expert Press
Release : 2018-08-23
ISBN : 1631573322
Language : En, Es, Fr & De

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Book Description :

Business Analytics: A Data-Driven Decision Making Approach for Business-Part I,/i> provides an overview of business analytics (BA), business intelligence (BI), and the role and importance of these in the modern business decision-making. The book discusses all these areas along with three main analytics categories: (1) descriptive, (2) predictive, and (3) prescriptive analytics with their tools and applications in business. This volume focuses on descriptive analytics that involves the use of descriptive and visual or graphical methods, numerical methods, as well as data analysis tools, big data applications, and the use of data dashboards to understand business performance. The highlights of this volume are: Business analytics at a glance; Business intelligence (BI), data analytics; Data, data types, descriptive analytics; Data visualization tools; Data visualization with big data; Descriptive analytics-numerical methods; Case analysis with computer applications.

Data Analytics for Organisational Development

Data Analytics for Organisational Development Book
Author : Uwe H. Kaufmann,Amy B. C. Tan
Publisher : John Wiley & Sons
Release : 2021-07-26
ISBN : 1119758335
Language : En, Es, Fr & De

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Book Description :

A practical guide for anyone who aspires to become data analytics–savvy Data analytics has become central to the operation of most businesses, making it an increasingly necessary skill for every manager and for all functions across an organisation. Data Analytics for Organisational Development: Unleashing the Potential of Your Data introduces a methodical process for gathering, screening, transforming, and analysing the correct datasets to ensure that they are reliable tools for business decision-making. Written by a Six Sigma Master Black Belt and a Lean Six Sigma Black Belt, this accessible guide explains and illustrates the application of data analytics for organizational development and design, with particular focus on Customer and Strategy Analytics, Operations Analytics and Workforce Analytics. Designed as both a handbook and workbook, Data Analytics for Organisational Development presents the application of data analytics for organizational design and development using case studies and practical examples. It aims to help build a bridge between data scientists, who have less exposure to actual business issues, and the "non-data scientists." With this guide, anyone can learn to perform data analytics tasks from translating a business question into a data science hypothesis to understanding the data science results and making the appropriate decisions. From data acquisition, cleaning, and transformation to analysis and decision making, this book covers it all. It also helps you avoid the pitfalls of unsound decision making, no matter where in the value chain you work. Follow the “Five Steps of a Data Analytics Case” to arrive at the correct business decision based on sound data analysis Become more proficient in effectively communicating and working with the data experts, even if you have no background in data science Learn from cases and practical examples that demonstrate a systematic method for gathering and processing data accurately Work through end-of-chapter exercises to review key concepts and apply methods using sample data sets Data Analytics for Organisational Development includes downloadable tools for learning enrichment, including spreadsheets, Power BI slides, datasets, R analysis steps and more. Regardless of your level in your organisation, this book will help you become savvy with data analytics, one of today’s top business tools.

Data Science for Business Professionals

Data Science for Business Professionals Book
Author : Probyto Data Science and Consulting Pvt. Ltd.
Publisher : BPB Publications
Release : 2020-05-06
ISBN : 9389423287
Language : En, Es, Fr & De

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Book Description :

Primer into the multidisciplinary world of Data Science KEY FEATURES - Explore and use the key concepts of Statistics required to solve data science problems - Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app - Learn how to build Data Science solutions with GCP and AWS DESCRIPTION The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset. WHAT WILL YOU LEARN - Understand the multi-disciplinary nature of Data Science - Get familiar with the key concepts in Mathematics and Statistics - Explore a few key ML algorithms and their use cases - Learn how to implement the basics of Data Pipelines - Get an overview of Cloud Computing & DevOps - Learn how to create visualizations using Tableau WHO THIS BOOK IS FOR This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science. TABLE OF CONTENTS 1. Data Science in Practice 2. Mathematics Essentials 3. Statistics Essentials 4. Exploratory Data Analysis 5. Data preprocessing 6. Feature Engineering 7. Machine learning algorithms 8. Productionizing ML models 9. Data Flows in Enterprises 10. Introduction to Databases 11. Introduction to Big Data 12. DevOps for Data Science 13. Introduction to Cloud Computing 14. Deploy Model to Cloud 15. Introduction to Business Intelligence 16. Data Visualization Tools 17. Industry Use Case 1 – FormAssist 18. Industry Use Case 2 – PeopleReporter 19. Data Science Learning Resources 20. Do It Your Self Challenges 21. MCQs for Assessments

Data Science For Dummies

Data Science For Dummies Book
Author : Lillian Pierson
Publisher : John Wiley & Sons
Release : 2015-02-20
ISBN : 1118841522
Language : En, Es, Fr & De

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Book Description :

Discover how data science can help you gain in-depth insight into your business – the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer covering all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad aspects of the topic, including the sometimes intimidating field of big data and data science, it is not an instructional manual for hands-on implementation. Here’s what to expect in Data Science for Dummies: Provides a background in big data and data engineering before moving on to data science and how it’s applied to generate value. Includes coverage of big data frameworks and applications like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL. Explains machine learning and many of its algorithms, as well as artificial intelligence and the evolution of the Internet of Things. Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate. It’s a big, big data world out there – let Data Science For Dummies help you get started harnessing its power so you can gain a competitive edge for your organization.

Data Science for Marketing Analytics

Data Science for Marketing Analytics Book
Author : Mirza Rahim Baig,Gururajan Govindan,Vishwesh Ravi Shrimali
Publisher : Packt Publishing Ltd
Release : 2021-09-07
ISBN : 1800563884
Language : En, Es, Fr & De

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Book Description :

This book on marketing analytics with Python will quickly get you up and running using practical data science and machine learning to improve your approach to marketing. You'll learn how to analyze sales, understand customer data, predict outcomes, and present conclusions with clear visualizations.

Machine Learning Optimization and Data Science

Machine Learning  Optimization  and Data Science Book
Author : Giuseppe Nicosia,Panos Pardalos,Giovanni Giuffrida,Renato Umeton,Vincenzo Sciacca
Publisher : Springer
Release : 2019-02-16
ISBN : 3030137090
Language : En, Es, Fr & De

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Book Description :

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The 46 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Data Science for Librarians

Data Science for Librarians Book
Author : Yunfei Du,Hammad Rauf Khan
Publisher : ABC-CLIO
Release : 2020-03-26
ISBN : 1440871221
Language : En, Es, Fr & De

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Book Description :

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Skills such as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design. Reviews fundamental concepts and principles of data science Offers a practical overview of tools and software Highlights skills and services needed in the 21st-century academic library Covers the entire research data life cycle and the librarian's role at each stage Provides insight into how library science and data science intersect

Business Data Science Combining Machine Learning and Economics to Optimize Automate and Accelerate Business Decisions

Business Data Science  Combining Machine Learning and Economics to Optimize  Automate  and Accelerate Business Decisions Book
Author : Matt Taddy
Publisher : McGraw-Hill Education
Release : 2019-08-23
ISBN : 9781260452778
Language : En, Es, Fr & De

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Book Description :

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: •Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling•Understand how use ML tools in real world business problems, where causation matters more that correlation•Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.

The Data Driven Leader

The Data Driven Leader Book
Author : Jenny Dearborn,David Swanson
Publisher : John Wiley & Sons
Release : 2017-11-06
ISBN : 1119382203
Language : En, Es, Fr & De

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Book Description :

Playing the blame game -- Leading with business outcomes -- Starting with analytics -- Early discoveries -- Diagnosing what's wrong -- The road ahead -- Results win support

Decision Intelligence For Dummies

Decision Intelligence For Dummies Book
Author : Pamela Baker
Publisher : John Wiley & Sons
Release : 2021-12-31
ISBN : 1119824869
Language : En, Es, Fr & De

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Book Description :

Learn to use, and not be used by, data to make more insightful decisions The availability of data and various forms of AI unlock countless possibilities for business decision makers. But what do you do when you feel pressured to cede your position in the decision-making process altogether? Decision Intelligence For Dummies pumps the brakes on the growing trend to take human beings out of the decision loop and walks you through the best way to make data-informed but human-driven decisions. The book shows you how to achieve maximum flexibility by using every available resource, and not just raw data, to make the most insightful decisions possible. In this timely book, you’ll learn to: Make data a means to an end, rather than an end in itself, by expanding your decision-making inquiries Find a new path to solid decisions that includes, but isn’t dominated, by quantitative data Measure the results of your new framework to prove its effectiveness and efficiency and expand it to a whole team or company Perfect for business leaders in technology and finance, Decision Intelligence For Dummies is ideal for anyone who recognizes that data is not the only powerful tool in your decision-making toolbox. This book shows you how to be guided, and not ruled, by the data.