Kindly note that we have put a lot of effort into researching the best books on Data Mining and Data Warehousing subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Data Mining and Data Warehousing" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
| 1. “Data Mining: Concepts and Techniques” by Han
“Data Mining: Concepts and Techniques” Book Review: This book provides an understanding and application of the theory and practice of discovering patterns hidden in large data sets. It also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. It addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases etc. The book provides a comprehensive and practical understanding of the concepts and techniques.The book is useful for anyone interested in learning powerful data mining techniques to meet real business challenges.
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| 2. “Data Warehousing” by Reema Thareja
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“Data Warehousing” Book Review: This book provides a thorough understanding of the fundamentals of data warehousing. The readers also get knowledge for creating and managing a data warehouse. The book introduces the various features and architecture of a data warehouse followed by a detailed study of the business requirements and dimensional modelling. It goes on to discuss the components of a data warehouse and then provides a thorough understanding of the building and maintenance of a data warehouse. The book includes several examples to illustrate concepts, contains several review questions and other end-chapter exercises to test the understanding of students. The book is designed for the students of Computer Science & Engineering (BE/Btech), computer applications (BCA/MCA) and computer science (B.Sc).
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| 3. “Data Warehousing and Data Mining” by Singh M
“Data Warehousing and Data Mining” Book Review: This book covers the basic concepts of data mining and warehousing. It also includes many case studies from experts in the field that provide a practical understanding of the subject matter to the students. The detailed explanations on the practical side with software tools such as Oracle BI, Weka and R are also included in the book. All the latest research trends in data mining such as ensemble learning, Web mining, bioinformatics and data warehousing with Oracle BI are discussed in detail. In addition it also discusses spatial data mining, big data, cloud computing and CRM. The book is useful for graduate and undergraduate students of computer science.
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| 4. “Data Mining and Warehousing” by S Prabhu
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“Data Mining and Warehousing” Book Review: This book provides a systematic introduction to the principles of Data Mining and Data Warehousing. It covers the entire range of data mining algorithms (prediction, classification and association), data mining products and applications, stages of implementing processes in detail. It gives an overall idea about ETL tools, Software Products, Schemas, Partition, Back up, Recovery and Tuning. It should be useful to undergraduate and postgraduate students of Computer Science and Information Technology. It will be useful for practitioners and research scholars.
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| 5. “Data Mining and Warehousing” by Khushboo and Sandeep
“Data Mining and Warehousing” Book Review: This book provides a comprehensive compilation of research available in this emerging and increasingly important field. The book offers tools, designs and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data and online analytical processing.It provides an overview of available approaches, techniques, open problems and applications related to data warehousing and mining. The book is designed for the students of Computer Science & Engineering (BE/Btech), computer applications (BCA/MCA) and computer science (B.Sc).
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| 6. “Introducing Data Science: Big Data, Machine Learning, and more, using Python tools” by Davy Cielen and Arno Meysman
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“Introducing Data Science: Big Data, Machine Learning, and more, using Python tools” Book Review: This book explains important data science concepts and teaches the readers how to accomplish the fundamental tasks that occupy data scientists. It describes important topics such as data visualization, graph databases, the use of NoSQL and the data science process. The readers will learn how Python allows to gain insights from big data sets that need to be stored on multiple machines. The book is useful for undergraduate and postgraduate students of Computer Science and Information Technology.
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| 7. “Data Warehousing: OLAP and Data Mining” by Nagabhushana S
“Data Warehousing: OLAP and Data Mining” Book Review: This book describes planning, managing, designing, implementing, supporting, maintaining and analyzing data warehouses in organizations. It also provides various mining techniques as well as issues in practical use of Data Mining Tools. The book is designed for IT students and professionals to learn or implement data warehousing technologies. It will also benefit the specialists, trainers and IT users.
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| 8. “Data Mining and Warehousing” by M Sudheep Elayidom
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“Data Mining and Warehousing” Book Review: This book covers the basic concepts of data mining and warehousing. It also includes many case studies from experts in the field that provide a practical understanding of the subject matter to the students. The detailed explanations on the practical side with software tools such as Oracle BI, Weka and R are also included in the book. All the latest research trends in data mining such as ensemble learning, Web mining, bioinformatics and data warehousing with Oracle BI are discussed in detail. In addition it also discusses spatial data mining, big data, cloud computing and CRM. The book is useful for graduate and undergraduate students of computer science.
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| 9. “Python for Data Science for Dummies” by John Paul Mueller and Luca Massaron
“Python for Data Science for Dummies” Book Review: This book teaches the advantage of Python programming to acquire, organize, process, and analyze large amounts of information to identify trends and patterns. It also describes how to apply basic concepts in the field of Python. It covers the fundamentals of Python data analysis programming and statistics. The book also focuses on important data science concepts like probability, random distributions, hypothesis testing and regression models. The readers will be able to apply statistical concepts such as probability and random distributions. The book is useful for data scientists as well as students who wish to learn Python and its applications.
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| 10. “The Encyclopedia of Data Warehousing and Mining” by John Wang
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“The Encyclopedia of Data Warehousing and Mining” Book Review: This book is a comprehensive study of data warehousing and mining. It provides a thorough examination of the issues of importance in the rapidly changing field of data warehousing and mining. It gives an overall idea about ETL tools, Software Products, Schemas, Partition, Back up, Recovery and Tuning. It should be useful to undergraduate and postgraduate students of Computer Science and Information Technology. It will be useful for practitioners and research scholars.
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