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Data Mining And Business Intelligence (Includes Practicals)

Data Mining And Business Intelligence (Includes Practicals)

          
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About the Book

The book introduces the concept of data mining as an important tool for enterprise data management and as a cutting edge technology for building competitive advantage. The readers will be able to effectively identify sources of data and process it for data mining and become well versed in all data mining algorithms, methods and tools. The coverage of the book will help you to analytically identify opportunities to derive business value from data.

· Introduction to Data Mining
· Data Exploration
· Data Preprocessing
· Classification
· Clustering
· Outlier Analysis
· Frequent Pattern Mining
· Introduction to Business Intelligence
· Decision Support System
· BI and Data Mining Applications

About the Author

S. K. Shinde is a Professor at Lokmanya Tilak College of Engineering, Navi Mumbai. Currently, he is working in the field of Programming; Web Mining; Frequent Pattern Discovery and Integration of domain knowledge, such as ontologies in the mining process and benefits of patterns in web personalized recommendations for ebusiness. Uddagiri Chandrasekhar has over 9 years of experience in software industry and academics. Currently working as Assistant professor-senior at VIT University, Vellore. He has few International publications and his active area of research is in Data Mining.



Table of Contents:
Chapter 1: Introduction to Data Mining 1.1 Definition of Data Mining 1.2 How Does Data Mining Work? 1.3 Architecture of Data Mining 1.4 Kinds of Data that can be mined 1.5 Data Mining Functionalities 1.6 Types of Data Mining Systems 1.7 Advantages of Data Mining 1.8 Disadvantages of Data Mining 1.9 Ethical Issues in Data Mining Chapter 2: Data Exploration 2.1 Data 2.2 Data Visualization Chapter 3: Data Preprocessing 3.1 Why Preprocessing? 3.2 Data Cleaning 3.3 Data Integration 3.4 Data Reduction 3.5 Data Transformation 3.6 Data Discretization and Concept Hierarchy Generation Chapter 4: Classification 4.1 Basic Concepts 4.2 Classification Methods 4.3 Prediction 4.4 Model Evaluation and Selection 4.5 Combining Classifiers (Ensemble Methods) Chapter 5: Clustering 5.1 Introducing Cluster Analysis 5.2 Clustering Methodologies Chapter 6: Outlier Analysis 6.1 Real-World Applications 6.2 Types of Outliers 6.3 Outlier Challenges 6.4 Outlier Detection Approaches 6.5 Outlier Detection Methods 6.6 Proximity-Based Outlier Analysis 6.7 Clustering-Based Outlier Analysis Chapter 7: Frequent Pattern Mining 7.1 Market Basket Analysis 7.2 Efficient and Scalable Frequent Item set Mining Methods 7.3 Mining Multilevel and Multidimensional Association Rules 7.4 Association Mining to Correlation Analysis Chapter 8: Introduction to Business Intelligence 8.1 Data, Information and Knowledge 8.2 Defining Business Intelligence 8.3 Important Factors in Business Intelligence 8.4 Business Intelligence Architecture 8.5 Business Intelligence Framework 8.6 Role of Mathematical Models in BI 8.7 Factors Responsible for a Successful BI Project 8.8 Development of BI System 8.9 Obstacles to Business Intelligence in an Organization 8.10 Ethics and Business Intelligence Chapter 9: Decision Support System 9.1 Concept of Decision Making 9.2 Techniques of Decision Making 9.3 Understanding Decision Support System (DSS) 9.4 Evolution of Information System 9.5 Development of Decision Support System 9.6 Application of DSS 9.7 Role of Business Intelligence in Decision Making Chapter 10: BI and Data Mining Applications 10.1 ERP and Business Intelligence 10.2 BI Applications in CRM 10.3 BI Applications in Marketing 10.4 BI Applications in Logistics and Production 10.5 Role of BI in Finance 10.6 BI Applications in Banking 10.7 BI Applications in Telecommunications 10.8 BI Applications in Fraud Detection 10.9 BI Applications in Clickstream Mining 10.10 BI Applications in the Retail Industry Summary Review Exercise Multiple Choice Questions Descriptive Questions Practicals Index


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Product Details
  • ISBN-13: 9789351197188
  • Publisher: Dreamtech Press
  • Binding: Paperback
  • No of Pages: 380
  • ISBN-10: 9351197182
  • Publisher Date: 2014
  • Language: English

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