1Chapter 1 Wholeness of Business Intelligence and Data Mining
80References
21.1 Business Intelligence
81 Chapter 9 Association Rule Mining
31.2 Pattern Recognition
829.1 Business Applications of Association Rules
41.3 Data Processing Chain
839.2 Representing Association Rules
5Quick Recap
849.3 Algorithms for Association Rules
6Questionnaire
859.4 Apriori Algorithm
7References
869.5 Creating Association Rules
8Chapter 2 Business Intelligence Concepts and its Applications
87Quick Recap
92.1 BI for Better Decisions
88Questionnaire
102.2 Decision Types
89References
112.3 BI Tools
90 Chapter 10 Text Mining
122.4 BI Skills
9110.1 Text Mining Applications
132.5 BI Applications
9210.2 Text Mining Process
14Quick Recap
9310.3 Mining the TDM
15Questionnaire
9410.4 Comparing Text Mining and Data Mining
16References
9510.5 Text Mining Best Practices
17Chapter 3 Data Warehousing
96Quick Recap
183.1 Design Considerations for DW
97Questionnaire
193.2 DW development Approaches
98References
203.3 DW Architecture
99Chapter 11 Web Mining
213.4 Data Sources
10011.1 Web Content Mining
223.5 Data Loading Processes
10111.2 Web Structure Mining
233.6 DW Design
10211.3 Web Usage Mining
243.7 DW Access
10311.4 Web Mining Algorithms
253.8 DW Best Practices
104Quick Recap
26Quick Recap
105Questionnaire
27Questionnaire
106References
28References
107Chapter 12 Big Data
29Chapter 4 Data Mining
10812.1 Definition of Big Data
304.1 Gathering and Selecting Data
10912.2 Big Data Landscape
314.2 Data Cleansing and Preparation
11012.3 Business Implications of Big Data
324.3 Outputs of Data Mining
11112.4 Technology Implications of Big Data
334.4 Evaluating Data Mining Results
11212.5 Big Data Technologies
344.5 Data Mining Techniques
11312.6 Management of Big Data
354.6 Tools and Platforms for Data Mining
114Quick Recap
364.7 Data Mining Best Practices
115Questionnaire
374.8 Myths about Data Mining
116References
384.9 Data Mining Mistakes
117Chapter 13 Data Modelling Primer
39Quick Recap
11813.1 Data Modelling Primer
40Questionnaire
11913.2 Evolution of Data Management Systems
41References
12013.3 Relational Data Models
42 Chapter 5 Decision Trees
12113.4 Implementing Relational Data Models
435.1 Decision Tree Problem
12213.5 DBMS
445.2 Decision Tree Construction
123Quick Recap
455.3 Lessons from Constructing Trees
124Questionnaire: References
465.4 Decision Tree Algorithms
125 Chapter 14 DM and BI: How do they Work Together?
47Quick Recap
12614.1 Introduction
48Questionnaire
12714.2 BI
49References
12814.3 Data Mining
50 Chapter 6 Regression
12914.4 Data Preparation
516.1 Correlations and Relationships
13014.5 Data Manipulation
526.2 Visual Look At Relationships
13114.6 Data Manipulation Language
536.3 Regression
13214.7 Data Mining VS Business Intelligence
546.4 Non Linear Regression
13314.8 Data Mining and Business Intelligence: How They Work Together
556.5 Logistic Regression
134Quick Recap
566.6 Advantages and Disadvantages of Regression Models
135Questionnaire
57Quick Recap
136References
58Questionnaire
137 Chapter 15 Data Profiling
59References
13815.1 Introduction
60 Chapter 7 Artificial Neural Networks
13915.2 Types of Data Profiling
617.1 Business Applications of ANN
14015.3 Steps in Data Profiling Process
627.2 Design Principles of ANN
14115.4 Benefits
637.3 Representation of ANN
14215.5 Challenges
647.4 Architecting a Neural Network
14315.6 Examples
657.5 Developing an ANN
14415.7 Tools
667.6 Advantages and Disadvantages of using ANN
145Quick Recap
67Quick Recap
146Questionnaire
68Questionnaire
147References
69References
148Chapter 16 How to Pair Data Mining and Business Intelligence in 2023
70Chapter 8 Cluster Analysis
14916.1 BI
718.1 Applications of Cluster Analysis
15016.2 How does data mining help business intelligence?
728.2 Definition of a Cluster
15116.3 What are the benefits of data mining in business intelligence?
738.3 Representing Clusters
15216.4 What are the challenges of data mining in business intelligence?
748.4 Clustering Techniques
15316.5 Which industries benefit the most from data mining in business intelligence?
758.5 K-means Algorithm For Clustering
154Quick Recap
768.6 Selecting the number of Clusters
155Questionnaire
778.7 Advantages and Disadvantages of K-means Algorithm
156References: Glossary
78Quick Recap
157Index
79Questionnaire
