Below is comprehensive list of Data Mining books at Amazon.com website which I scraped using ScraperWiki (free online data scraper shared with the world).
1. Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)
2. Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)
3. Introduction to Data Mining
4. Handbook of Statistical Analysis and Data Mining Applications
5. Data Analysis with Open Source Tools
6. Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
7. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
8. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
9. Data Mining with R: Learning with Case Studies (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
10. Data Analysis Using SQL and Excel
11. Data Mining: Concepts and Techniques, Second Edition (The Morgan Kaufmann Series in Data Management Systems)
12. Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
13. Head First Data Analysis: A Learner’s Guide to Big Numbers, Statistics, and Good Decisions
14. Data Mining Techniques in CRM: Inside Customer Segmentation
15. Data Mining with Microsoft SQL Server 2008
16. Principles of Data Mining (Undergraduate Topics in Computer Science)
17. Mastering Data Mining: The Art and Science of Customer Relationship Management
18. Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know
19. Data Mining and Statistics for Decision Making (Wiley Series in Computational Statistics)
20. Handbook of Statistical Analysis and Data Mining Applications
21. Data Mining: A Tutorial Based Primer
22. Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition
23. Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis
24. Data Mining: Concepts, Models, Methods, and Algorithms
25. Machine Learning: An Algorithmic Perspective (Chapman & Hall/Crc Machine Learning & Pattern Recognition)
26. Principles of Data Mining (Adaptive Computation and Machine Learning)
27. Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management
28. Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
29. Programming Collective Intelligence: Building Smart Web 2.0 Applications
30. Beautiful Data: The Stories Behind Elegant Data Solutions
31. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
32. Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics)
33. Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems)
34. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
35. Intelligent Data Analysis
36. Beautiful Visualization: Looking at Data through the Eyes of Experts (Theory in Practice)
37. The Top Ten Algorithms in Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
38. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (The Morgan Kaufmann Series in Data Management Systems)
39. 21 Recipes for Mining Twitter
40. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R)
41. Data Mining Using SAS Enterprise Miner: A Case Study Approach
42. Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies
43. Discovering Knowledge in Data: An Introduction to Data Mining
44. Practical Applications of Data Mining
45. Data Mining: Introductory and Advanced Topics
46. Mining the Web: Discovering Knowledge from Hypertext Data
47. How to Measure Anything: Finding the Value of Intangibles in Business
48. Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions (Synthesis Lectures on Data Min)
49. Data Analysis with Open Source Tools
50. Modern Data Warehousing, Mining, and Visualization: Core Concepts
51. A Practitioner’s Guide to Resampling for Data Analysis, Data Mining, and Modeling
52. Data Mining Methods and Models
53. Text Mining Application Programming (Charles River Media Programming)
54. Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications
55. Temporal Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
56. Microsoft® SQL Server 2008 R2 Analytics & Data Visualization
57. Data Analysis Using SQL and Excel
58. Data Mining and Machine Learning in Cybersecurity
59. Data Preparation for Data Mining Using SAS (The Morgan Kaufmann Series in Data Management Systems)
60. Data Preparation for Analytics Using SAS (SAS Press)
61. Practical Data Mining
62. Clinical Data-Mining: Integrating Practice and Research (Pocket Guides to Social Work Research Methods)
63. Business Intelligence: Data Mining and Optimization for Decision Making
64. Text Mining: Applications and Theory
65. Data Mining Methods for the Content Analyst: An Introduction to the Computational Analysis of Content (Routledge Communication Series)
66. Introduction to Business Data Mining
67. Mining the Social Web
68. Data Mining for Genomics and Proteomics: Analysis of Gene and Protein Expression Data (Wiley Series on Methods and Applications in Data Mining)
69. Hadoop: The Definitive Guide
70. Understanding Complex Datasets: Data Mining with Matrix Decompositions (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
71. Functional Data Analysis with R and MATLAB (Use R)
72. Machine Learning and Data Mining for Computer Security: Methods and Applications (Advanced Information and Knowledge Processing)
73. Data Mining and Knowledge Discovery Handbook (Springer series in solid-state sciences)
74. Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms)
75. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage
76. Practical Text Mining with Perl (Wiley Series on Methods and Applications in Data Mining)
77. Predictive Data Mining: A Practical Guide (The Morgan Kaufmann Series in Data Management Systems)
78. Data Warehousing For Dummies
79. The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
80. Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis
81. Data Warehousing Essentials (ABC’s of Data Warehousing & Data Mining)
82. Investigative Data Mining for Security and Criminal Detection
83. Handbook of Educational Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
84. Data Mining: Multimedia, Soft Computing, and Bioinformatics
85. Making Sense of Data II: A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
86. Music Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
87. Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations
88. Data Mining and Business Intelligence: A Guide to Productivity
89. Social Network Data Analytics
90. Data Mining and Knowledge Discovery with Evolutionary Algorithms
91. Beautiful Data
92. Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms
93. Exploratory Data Mining and Data Cleaning
94. Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
95. Data Mining and Uncertain Reasoning: An Integrated Approach
96. Microsoft PowerPivot for Excel 2010: Give Your Data Meaning
97. Applied Data Mining for Business and Industry (Statistics in Practice)
98. Discovering Data Mining: From Concept to Implementation
99. Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel(R) with 100.
100. XLMiner(TM) + Making Sense of Data Set
101. Introduction to Clustering Large and High-Dimensional Data
102. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
103. Data Mining and Knowledge Discovery via Logic-Based Methods: Theory, Algorithms, and Applications (Springer Optimization and Its Applications)
104. International Journal of Data Mining and Bioinformatics
105. Building Data Mining Applications for CRM
106. Visual Data Mining: Techniques and Tools for Data Visualization and Mining
107. Text Mining: Predictive Methods for Analyzing Unstructured Information
108. Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management
109. Java Data Mining: Strategy, Standard, and Practice: A Practical Guide for architecture, design, and implementation (The Morgan Kaufmann Series in Data Management Systems)
110. Mining the Talk: Unlocking the Business Value in Unstructured Information
Minecraft Foam Pickaxe
111. Data Mining Powerpoint Templates – Data Mining Powerpoint Background – Data Mining PPT Templates
Business Modeling and Data Mining (The Morgan Kaufmann Series in Data Management Systems)
112. Mining the Web: Transforming Customer Data into Customer Value
113. Scientific Data Mining: A Practical Perspective
114. Data Mining Cookbook: Modeling Data for Marketing, Risk, and Customer Relationship Management (Datawarehousing)
115. Applying and evaluating models to predict customer attrition using data mining techniques.: An article from: Journal of Comparative International Management
116. Research and Development in Knowledge Discovery and Data Mining: Second Pacific-Asia Conference, PAKDD’98, Melbourne, Australia, April 15-17, 1998, Proceedings
117. Research and Trends in Data Mining Technologies and Applications
118. Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
119. Optimization Based Data Mining: Theory and Applications (Advanced Information and Knowledge Processing)
120. Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics (The Springer International Series in Engineering and Computer Science)
121. Spatial and Spatiotemporal Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
122. Statistical Analysis of Network Data: Methods and Models (Springer Series in Statistics)
123. Data Mining for Design and Manufacturing: Methods and Applications
124. Introduction to Data Technologies (Chapman & Hall/CRC Computer Science & Data Analysis)
125. Data Clustering in C++: An Object-Oriented Approach (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
126. Data Mining Using SAS Enterprise Miner:
127. Advances in Machine Learning and Data Mining for Astronomy (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
128. Grouping Multidimensional Data: Recent Advances in Clustering
129. Algorithms of the Intelligent Web
130. Social Computing: A Data Mining Perspective (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
131. Agents and Data Mining: Interaction and Integration (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
132. Spectral Feature Selection for Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
133. Cluster Effects in Mining Complex Data
134. Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends
135. Data Mining: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications (Intelligent Systems Reference Library)