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Item #:
3718449
Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
83% of respondents would recommend this to a friend
Item #:
3718449
GTQ 1013
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Data Mining for Business Analytics is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics
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What Stands Out
Comprehensive Coverage
This edition delivers extensive insights into data mining concepts, techniques, and applications, making it ideal for both beginners and seasoned professionals looking to enhance their business analytics skills using XLMiner.
Practical Application
The book integrates practical examples and hands-on exercises with XLMiner, allowing readers to apply theoretical concepts directly to real-world business problems, fostering deeper understanding and skill development.
Updated Content
Featuring the latest advancements in data mining, this edition ensures readers are equipped with cutting-edge techniques, keeping them competitive in the rapidly evolving field of business analytics.
Product Details
- Comprehensive coverage of data mining methods using XLMiner® for Education software
- Includes updated topics such as text mining, social network analysis, and ensemble methods
- Real-world examples and data-rich case studies for practical understanding
- Ideal textbook for upper-undergraduate and graduate-level courses in data mining and analytics
- Written by renowned experts in the field of data mining and business analytics
- Authors have extensive experience in teaching, research, and application of statistical and data mining methods
| Publisher | WILEY |
| Publication date | January 1, 2016 |
| Edition | 3rd |
| Language | English |
| Print length | 552 pages |
| ISBN-10 | 1118729277 |
| ISBN-13 | 978-1118729274 |
| Item Weight | 2.32 pounds (1.05 kg) |
| Dimensions | 7.1 x 1.2 x 9.9 inches (18 x 3 x 25.1 cm) |
Who Should Buy?
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Business Analysts
Ideal for analysts looking to leverage data mining techniques for improved decision-making and predictive modeling.
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Students and Educators
Beneficial for those studying business analytics and data mining, providing practical examples and hands-on exercises.
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Data Science Professionals
Useful for practitioners needing to understand data mining applications and enhance their analytical skill set using XLMiner.
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Casual Users
Not suitable for individuals seeking quick insights without a foundational understanding of data analysis concepts.
Product Description
Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
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Probability & Statistics Editorial Review
**** The third edition of "Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner" presents a mixed yet generally positive reception among readers. Many users appreciate its clear explanations of fundamental data science and machine learning concepts, often noting it as a valuable resource for those looking to understand XLMiner and its application in business analytics. The book is highlighted for its straightforward approach, which allows for both quick skimming and in-depth study, making it suitable for various levels of expertise. Readers have found that the book serves as an effective guide for using statistical functions within XLMiner, with some particularly praising its ability to simplify complex topics. However, there are suggestions for improvement, particularly regarding the depth and quality of examples provided, especially in relation to executing functions within Excel. While some students have reported success in using the book alongside other software like R, others have expressed dissatisfaction due to perceived convoluted language and lack of clarity in the core examples. This has led to a more critical assessment from a few users who found the text lacking and difficult to follow. Overall, the book is recommended for those specifically looking to learn about XLMiner in the context of data mining, but potential readers may want to Consider the mixed feedback on the quality of examples and clarity of explanations. **Pros and Cons:** **
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Pros
- Clear explanations of fundamental concepts.
- Useful as a guide for XLMiner software.
- Suitable for both skimming and deeper study.
- Appreciated for simplifying complex topics.
- Rich examples for most concepts.
Cons
- Some examples may lack clarity in executing in Excel.
Product Price History
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GTQ 1013
Order now and get it around Friday, October 23
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Features & Benefits
- Applied approach to data mining and predictive analytics
- Real-life case studies and hands-on exercises
- Coverage on text mining, social network analysis, collaborative filtering, ensemble methods, and uplift modeling
- Ideal for upper-undergraduate and graduate-level courses in data mining and predictive modeling
- Suitable for professionals working with predictive analytics in various fields
- Free 140-day license to use XLMiner for Education software included
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