An Introduction to Business Analytics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download An Introduction to Business Analytics PDF full book. Access full book title An Introduction to Business Analytics by Ger Koole. Download full books in PDF and EPUB format.
Author: Ger Koole
Publisher: Lulu.com
ISBN: 9082017938
Category : Computers
Languages : en
Pages : 174
Get Book
Book Description
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.
Author: Ger Koole
Publisher: Lulu.com
ISBN: 9082017938
Category : Computers
Languages : en
Pages : 174
Get Book
Book Description
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.
Author: Andrew Goodnite
Publisher:
ISBN: 9781792424953
Category :
Languages : en
Pages :
Get Book
Book Description
Author: A Ohri
Publisher: Springer Science & Business Media
ISBN: 1461443423
Category : Business & Economics
Languages : en
Pages : 322
Get Book
Book Description
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.
Author: Adam Fleischhacker
Publisher:
ISBN:
Category :
Languages : en
Pages : 298
Get Book
Book Description
This up-to-date business analytics textbook (published in July 2020) will get you harnessing the power of the R programming language to: manipulate and model data, discover and communicate insight, to visually communicate that insight, and successfully advocate for change within an organization. Book Description A frequent teaching-award winning professor with an analytics-industry background shares his hands-on guide to learning business analytics. It is the first textbook addressing a complete and modern business analytics workflow that includes data manipulation, data visualization, modelling business problems with graphical models, translating graphical models into code, and presenting insights back to stakeholders. Book Highlights Content that is accessible to anyone, even most analytics beginners. If you have taken a stats course, you are good to go. Assumes no knowledge of the R programming language. Provides introduction to R, RStudio, and the Tidyverse. Provides a solid foundation and an implementable workflow for anyone wading into the Bayesian inference waters. Provides a complete workflow within the R-ecosystem; there is no need to learn several programming languages or work through clunky interfaces between software tools. First book introducing two powerful R-packages - `causact` for visual modelling of business problems and `greta` which is an R interface to `TensorFlow` used for Bayesian inference. Uses the intuitive coding practices of the `tidyverse` including using `dplyr` for data manipulation and `ggplot2` for data visualization. Datasets that are freely and easily accessible. Code for generating all results and almost every visualization used in the textbook. Do not learn statistical computation or fancy math in a vacuum, learn it through this guide within the context of solving business problems.
Author: Johannes Ledolter
Publisher: John Wiley & Sons
ISBN: 1118572157
Category : Computers
Languages : en
Pages : 368
Get Book
Book Description
Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are provided with the neededguidance to model and interpret complicated data and become adeptat building powerful models for prediction and classification. Highlighting both underlying concepts and practicalcomputational skills, Data Mining and Business Analytics withR begins with coverage of standard linear regression and theimportance of parsimony in statistical modeling. The book includesimportant topics such as penalty-based variable selection (LASSO);logistic regression; regression and classification trees;clustering; principal components and partial least squares; and theanalysis of text and network data. In addition, the bookpresents: • A thorough discussion and extensive demonstration of thetheory behind the most useful data mining tools • Illustrations of how to use the outlined concepts inreal-world situations • Readily available additional data sets and related Rcode allowing readers to apply their own analyses to the discussedmaterials • Numerous exercises to help readers with computing skillsand deepen their understanding of the material Data Mining and Business Analytics with R is an excellentgraduate-level textbook for courses on data mining and businessanalytics. The book is also a valuable reference for practitionerswho collect and analyze data in the fields of finance, operationsmanagement, marketing, and the information sciences.
Author: Daniel S. Putler
Publisher: CRC Press
ISBN: 146650398X
Category : Business & Economics
Languages : en
Pages : 315
Get Book
Book Description
Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the tex
Author: S. Christian Albright
Publisher:
ISBN: 9789814878180
Category : Decision making
Languages : en
Pages : 882
Get Book
Book Description
Author: Jean-Paul Isson
Publisher: John Wiley & Sons
ISBN: 1118417089
Category : Business & Economics
Languages : en
Pages : 416
Get Book
Book Description
Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice. Provides the essential concept and framework to implement business analytics Written clearly for a nontechnical audience Filled with case studies across a variety of industries Uniquely focuses on integrating multiple types of big data intelligence into your business Companies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, Win with Advanced Analytics provides a comprehensive framework and applications of how to leverage business analytics/big data to outpace the competition.
Author: Walter R. Paczkowski
Publisher: Springer Nature
ISBN: 3030870235
Category : Business & Economics
Languages : en
Pages : 416
Get Book
Book Description
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
Author: Bernard Marr
Publisher: Pearson UK
ISBN: 1292017465
Category : Business & Economics
Languages : en
Pages : 312
Get Book
Book Description
Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimize their internal processes and identify cost savings and growth opportunities. It includes analysis techniques within the following categories: Financial analytics – cashflow, profitability, sales forecasts Market analytics – market size, market trends, marketing channels Customer analytics – customer lifetime values, social media, customer needs Employee analytics – capacity, performance, leadership Operational analytics – supply chains, competencies, environmental impact Bare business analytics – sentiments, text, correlations Each tool will follow the bestselling Key format of being 5-6 pages long, broken into short sharp advice on the essentials: What is it? When should I use it? How do I use it? Tips and pitfalls Further reading This essential toolkit also provides an invaluable section on how to gather original data yourself through surveys, interviews, focus groups, etc.
