Introduction to R for Business Intelligence
(eBook)

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Published
Packt Publishing, 2018.
Status
Available Online

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Format
eBook
Language
English
ISBN
9781785286513

Citations

APA Citation, 7th Edition (style guide)

Jay Gendron., & Jay Gendron|AUTHOR. (2018). Introduction to R for Business Intelligence . Packt Publishing.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Jay Gendron and Jay Gendron|AUTHOR. 2018. Introduction to R for Business Intelligence. Packt Publishing.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Jay Gendron and Jay Gendron|AUTHOR. Introduction to R for Business Intelligence Packt Publishing, 2018.

MLA Citation, 9th Edition (style guide)

Jay Gendron, and Jay Gendron|AUTHOR. Introduction to R for Business Intelligence Packt Publishing, 2018.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work IDc9c28860-a11c-85b7-6275-e6542691a22c-eng
Full titleintroduction to r for business intelligence
Authorgendron jay
Grouping Categorybook
Last Update2023-04-05 18:45:54PM
Last Indexed2024-03-27 05:58:21AM

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First LoadedJul 14, 2022
Last UsedMar 15, 2024

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    [synopsis] => Key Features
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.
Book Description
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.
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