Mastering Business Analytics With R
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Mastering Business Analytics With R
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Author : Dr. Bala Saraswathi Atluri
language : en
Publisher: OrangeBooks Publication
Release Date : 2025-01-31
Mastering Business Analytics With R written by Dr. Bala Saraswathi Atluri and has been published by OrangeBooks Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Business & Economics categories.
This book offers a comprehensive guide to mastering business analytics with R, focusing on its critical role in data-driven decision-making across various sectors, including HR, marketing, finance, and more. It provides readers with foundational knowledge of business analytics, illustrating its importance and use cases in diverse functional areas. The book covers data visualization, non-parametric tests, and intermediate multivariate analysis, enabling readers to use R effectively. Students will learn to install R, perform operations, and conduct parametric and non-parametric tests to support informed decisions. Advanced topics such as cluster and factor analysis are also included to deepen analytical skills.
Mastering Predictive Analytics With R
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Author : James D. Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-08-18
Mastering Predictive Analytics With R written by James D. Miller and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-18 with Computers categories.
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R. Style and approach This book takes a step-by-step approach in explaining the intermediate to advanced concepts in predictive analytics. Every concept is explained in depth, supplemented with practical examples applicable in a real-world setting.
Mastering Predictive Analytics With R
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Author : Rui Miguel Forte
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-06-17
Mastering Predictive Analytics With R written by Rui Miguel Forte and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Computers categories.
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.
Mastering Business Intelligence Bi
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date :
Mastering Business Intelligence Bi written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unleash the Power of Data with "Mastering Business Intelligence (BI)" In today's data-driven world, businesses rely on Business Intelligence (BI) to transform raw data into actionable insights. BI professionals are at the forefront of this revolution, enabling organizations to make informed decisions and gain a competitive edge. "Mastering Business Intelligence (BI)" is your comprehensive guide to excelling in the world of BI, providing you with the knowledge, skills, and strategies to become a data-savvy expert. Your Path to BI Excellence Business Intelligence is not just about collecting data; it's about turning it into meaningful information and driving strategic outcomes. Whether you're new to BI or an experienced professional aiming to sharpen your skills, this book will empower you to master the art of Business Intelligence. What You Will Discover BI Fundamentals: Gain a deep understanding of BI concepts, methodologies, and tools, from data warehousing to data visualization. Data Analysis: Dive into data analysis techniques, data modeling, and data manipulation to extract valuable insights from diverse datasets. Data Visualization: Learn the art of storytelling through data with effective data visualization and reporting techniques. BI Tools and Technologies: Explore popular BI tools like Tableau, Power BI, and QlikView, and discover how to leverage them for maximum impact. Data Governance and Ethics: Understand the importance of data governance, data quality, and ethical considerations in BI. Career Advancement: Explore career pathways in the BI field and learn how mastering BI can open doors to exciting job opportunities. Why "Mastering Business Intelligence (BI)" Is Essential Comprehensive Coverage: This book provides comprehensive coverage of BI topics, ensuring you have a well-rounded understanding of BI concepts and applications. Expert Guidance: Benefit from insights and advice from experienced BI professionals and industry experts who share their knowledge and best practices. Career Advancement: BI offers a wide range of career opportunities, and this book will help you unlock your full potential in this dynamic field. Stay Ahead: In a data-driven world, mastering BI is vital for staying competitive and contributing to data-driven decision-making. Your Journey to BI Mastery Begins Here "Mastering Business Intelligence (BI)" is your roadmap to excelling in the world of BI and advancing your career. Whether you aspire to be a BI analyst, data scientist, or BI consultant, this guide will equip you with the skills and knowledge to achieve your goals. "Mastering Business Intelligence (BI)" is the ultimate resource for individuals seeking to excel in the world of Business Intelligence. Whether you are new to BI or looking to enhance your skills, this book will provide you with the knowledge and strategies to become a data-savvy expert. Don't wait; begin your journey to BI mastery today! © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
The Modern Business Data Analyst
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Author : Dominik Jung
language : en
Publisher: Springer Nature
Release Date : 2024-07-03
The Modern Business Data Analyst written by Dominik Jung and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-03 with Computers categories.
This book illustrates and explains the key concepts of business data analytics from scratch, tackling the day-to-day challenges of a business data analyst. It provides you with all the professional tools you need to predict online shop sales, to conduct A/B tests on marketing campaigns, to generate automated reports with PowerPoint, to extract datasets from Wikipedia, and to create interactive analytics Web apps. Alongside these practical projects, this book provides hands-on coding exercises, case studies, the essential programming tools and the CRISP-DM framework which you'll need to kickstart your career in business data analytics. The different chapters prioritize practical understanding over mathematical theory, using realistic business data and challenges of the Junglivet Whisky Company to intuitively grasp key concepts and ideas. Designed for beginners and intermediates, this book guides you from business data analytics fundamentals to advanced techniques, covering a large number of different techniques and best-practices which you can immediately exploit in your daily work. The book does not assume that you have an academic degree or any experience with business data analytics or data science. All you need is an open mind, willingness to puzzle and think mathematically, and the willingness to write some R code. This book is your all-in-one resource to become proficient in business data analytics with R, equipped with practical skills for the real world.
Business Analysis Essentials
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Author : Virversity Online Courses
language : en
Publisher: eBookIt.com
Release Date : 2025-03-26
Business Analysis Essentials written by Virversity Online Courses and has been published by eBookIt.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Business & Economics categories.
Business Analysis Essentials is a comprehensive online course designed to equip aspiring business analysts with the necessary skills and knowledge to excel in the field. Through a series of targeted lessons, students will gain a deep understanding of business analysis principles and develop the ability to communicate effectively with stakeholders, gather and document requirements, and leverage data for informed decision-making. Master Business Analysis Techniques and Strategies Gain foundational knowledge of business analysis roles and specializations. Enhance communication skills for successful stakeholder engagement. Learn essential techniques for requirement gathering and documentation. Understand how to model business processes and conduct SWOT and Gap analyses. Develop data-driven decision-making skills using key analysis tools. Comprehensive Training in Business Analysis Core Skills Business Analysis Essentials starts with an introduction to the fundamental principles and roles of a business analyst. Understanding these basics is crucial for anyone looking to thrive in a business analysis career. Students will explore the different types of business analysts and specializations, providing insight into various career paths within the profession. Throughout the course, emphasis is placed on communication techniques needed to interact effectively with stakeholders. Lessons will focus on identifying and engaging stakeholders, ensuring that participants develop the skills necessary for successful collaborations. Requirement gathering and documentation practices are also covered extensively, enabling students to learn industry best practices.The course delves into specific analysis techniques, such as Business Process Modeling, SWOT Analysis, and Gap Analysis. These will enable students to visualize business processes and identify areas for improvement. Solution evaluation is another key topic, equipping participants with the skills needed to assess business needs and propose viable solutions.In the realm of data analysis, students will learn data collection and interpretation basics, followed by leveraging this information for insightful decision-making. The course also introduces common business analysis tools, empowering students to utilize technology effectively in their analysis work.By learning how to create effective business cases and develop business requirement documents, course participants will be able to justify business investments and document essential elements with clarity. Change management and performance evaluation lessons are included to round out the well-rounded curriculum.Upon completing Business Analysis Essentials, students will emerge as confident and knowledgeable business analysts, equipped to make meaningful contributions to any organization. They will possess a solid foundation in both theory and practical application, ready to drive business success through thoughtful analysis and strategic insights.
Mastering The Sap Business Information Warehouse
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Author : Kevin McDonald
language : en
Publisher: John Wiley & Sons
Release Date : 2002-10-02
Mastering The Sap Business Information Warehouse written by Kevin McDonald and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-10-02 with Computers categories.
"This book is insightful and thought-provoking for even the most seasoned SAP BW individual." —Richard M. Dunning, Chair, American SAP Users Group Written by the leading experts in the field, this comprehensive guide shows you how to implement the SAP Business Information Warehouse (BW) and create useful applications for business analysis of company-wide data. You'll quickly learn how to design, build, analyze, and administer the data and information in the SAP BW component. The authors present the material in a way that reflects the process an organization goes through during a software implementation. They begin with an introduction to the fundamentals of data warehousing and business intelligence, helping you determine if SAP BW is right for your organization. The book then focuses on the business content and options available when trying to deliver value from the data stored in the SAP BW. And it includes a methodology for implementing the BW, such as data modeling and techniques for capturing and transforming data. With this book, you'll discover the options available in SAP BW 3.0 and explore a new way to drive business performance. It will show you how to: Tackle such challenges as eliminating poor data quality Develop an information model in order to properly deploy SAP BW Utilize ETL, data storage, information access, analysis, and presentation services Schedule, monitor, archive, and troubleshoot data loads Effectively plan and manage the performance of a data warehouse The companion Web site provides useful guides and templates for configuring your system, industry case studies, and additional updates.
R For Programmers
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Author : Dan Zhang
language : en
Publisher: CRC Press
Release Date : 2017-03-31
R For Programmers written by Dan Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Mathematics categories.
This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective methdologies in traditional programing to R programing. It shows how to interface R with C, Java, and other popular programing laguages and platforms.
Modern Business Analytics
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Author : Deanne Larson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-12-17
Modern Business Analytics written by Deanne Larson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-17 with Business & Economics categories.
Deriving business value from analytics is a challenging process. Turning data into information requires a business analyst who is adept at multiple technologies including databases, programming tools, and commercial analytics tools. This practical guide shows programmers who understand analysis concepts how to build the skills necessary to achieve business value. Author Deanne Larson, data science practitioner and academic, helps you bridge the technical and business worlds to meet these requirements. You'll focus on developing these skills with R and Python using real-world examples. You'll also learn how to leverage methodologies for successful delivery. Learning methodology combined with open source tools is key to delivering successful business analytics and value. This book shows you how to: Apply business analytics methodologies to achieve successful results Cleanse and transform data using R and Python Use R and Python to complete exploratory data analysis Create predictive models to solve business problems in R and Python Use Python, R, and business analytics tools to handle large volumes of data Commit code to GitHub to collaborate with data engineers and data scientists Measure success in business analytics
A User S Guide To Business Analytics
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Author : Ayanendranath Basu
language : en
Publisher: CRC Press
Release Date : 2016-08-19
A User S Guide To Business Analytics written by Ayanendranath Basu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-19 with Business & Economics categories.
A User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are developed from a fairly basic level to accommodate readers who have limited training in the theory of statistics. A substantial number of case studies and numerical illustrations using the R-software package are provided for the benefit of motivated beginners who want to get a head start in analytics as well as for experts on the job who will benefit by using this text as a reference book. The book is comprised of 12 chapters. The first chapter focuses on business analytics, along with its emergence and application, and sets up a context for the whole book. The next three chapters introduce R and provide a comprehensive discussion on descriptive analytics, including numerical data summarization and visual analytics. Chapters five through seven discuss set theory, definitions and counting rules, probability, random variables, and probability distributions, with a number of business scenario examples. These chapters lay down the foundation for predictive analytics and model building. Chapter eight deals with statistical inference and discusses the most common testing procedures. Chapters nine through twelve deal entirely with predictive analytics. The chapter on regression is quite extensive, dealing with model development and model complexity from a user’s perspective. A short chapter on tree-based methods puts forth the main application areas succinctly. The chapter on data mining is a good introduction to the most common machine learning algorithms. The last chapter highlights the role of different time series models in analytics. In all the chapters, the authors showcase a number of examples and case studies and provide guidelines to users in the analytics field.