Introduction To R For Business Intelligence
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Introduction To R For Business Intelligence
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Author :
language : en
Publisher:
Release Date : 2016
Introduction To R For Business Intelligence written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Introduction To R For Business Intelligence
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Author : Jay Gendron
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-08-26
Introduction To R For Business Intelligence written by Jay Gendron 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 2016-08-26 with Computers categories.
Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions—and all of this with the help of real-life examples.
R For Business Analytics
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Author : A Ohri
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-14
R For Business Analytics written by A Ohri and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-14 with Business & Economics categories.
This book examines common tasks performed by business analysts and helps the reader navigate the wealth of information in R and its 4000 packages to create useful analytics applications. Includes interviews with corporate users of R, and easy-to-use examples.
Business Intelligence
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Author : Rimvydas Skyrius
language : en
Publisher: Springer Nature
Release Date : 2021-03-08
Business Intelligence written by Rimvydas Skyrius and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-08 with Computers categories.
This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics.
Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-14
Data Mining For Business Analytics written by Galit Shmueli 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 2019-10-14 with Mathematics categories.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Data Mining And Business Analytics With R
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Author : Johannes Ledolter
language : en
Publisher: John Wiley & Sons
Release Date : 2013-05-28
Data Mining And Business Analytics With R written by Johannes Ledolter 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 2013-05-28 with Mathematics categories.
Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools Illustrations of how to use the outlined concepts in real-world situations Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences.
Introduction To R For Business Intelligence
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Author : Jay Gendron
language : en
Publisher:
Release Date : 2016
Introduction To R For Business Intelligence written by Jay Gendron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Business planning categories.
Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions - and all of this with the help of real-life examples.
Practical Business Intelligence
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Author : Ahmed Sherif
language : en
Publisher: Packt Publishing
Release Date : 2016-12-21
Practical Business Intelligence written by Ahmed Sherif and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-21 with Computers categories.
Learn to get the most out of your business data to optimize your business About This Book This book will enable and empower you to break free of the shackles of spreadsheets Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide This book includes real-world use cases that teach you how analytics can be put to work to optimize your business Using a fictional transactional dataset in raw form, you'll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform Who This Book Is For This book is for anyone who has wrangled with data to try to perform automated data analysis through visualizations for themselves or their customers. This highly-customized guide is for developers who know a bit about analytics but don't know how to make use of it in the field of business intelligence. What You Will Learn Create a BI environment that enables self-service reporting Understand SQL and the aggregation of data Develop a data model suitable for analytical reporting Connect a data warehouse to the analytic reporting tools Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python Get to know the best practices to develop various reports and applications when using BI tools Explore the field of data analysis with all the data we will use for reporting In Detail Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market. Style and approach Packed with real-world examples, this pragmatic guide helps you polish your data and make informed decisions for your business. We cover both business and data analysis perspectives, blending theory and practical hands-on work so that you perceive data as a business asset."
Business Analysis For Business Intelligence
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Author : Bert Brijs
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Business Analysis For Business Intelligence written by Bert Brijs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
Aligning business intelligence (BI) infrastructure with strategy processes not only improves your organization's ability to respond to change, but also adds significant value to your BI infrastructure and development investments. Until now, there has been a need for a comprehensive book on business analysis for BI that starts with a macro view and
An Introduction To Business Analytics
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Author : Ger Koole
language : en
Publisher: Lulu.com
Release Date : 2019
An Introduction To Business Analytics written by Ger Koole and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Computers categories.
Business Analytics (BA) is about turning data into decisions. This book covers the full range of BA topics, including statistics, machine learning and optimization, in a way that makes them accessible to a broader audience. Decision makers will gain enough insight into the subject to have meaningful discussions with machine learning specialists, and those starting out as data scientists will benefit from an overview of the field and take their first steps as business analytics specialist. Through this book and the various exercises included, you will be equipped with an understanding of BA, while learning R, a popular tool for statistics and machine learning.