More Details Original Title. Other Editions 1. Friend Reviews. To see what your friends thought of this book, please sign up. Lists with This Book. This book is not yet featured on Listopia. Add this book to your favorite list ». Community Reviews. Showing Average rating 3. Rating details. More filters. Sort order. May 30, Monishaadevi rated it it was amazing. This review has been hidden because it contains spoilers. To view it, click here.
Jun 26, Rajat Sharma rated it liked it. Jan 11, Suri rated it liked it. Dec 18, Velu rated it really liked it Shelves: warehouse. Nice book. Jun 27, Shobhit Dogra rated it it was amazing. Jul 02, Avinash Choudhary marked it as to-read. Best book to understand olap model. Dec 22, Priyanka Palaniyappan added it. Feb 12, Rk added it Shelves: dmw. The papers are organized in topical sections on conceptual design and modeling, olap and cube processing, distributed data warehouse, data privacy in data warehouse, data warehouse and data mining, clustering, mining data streams, classification, text mining and taxonomy, machine learning techniques, and data mining applications.
Find out the basics of data warehousing and how it facilitates data mining and business intelligence with Data Warehousing For Dummies, 2nd Edition. The fully updated Second Edition of Data Warehousing For Dummies helps you understand, develop, implement, and use data warehouses, and offers a sneak peek into their future. Data Warehousing and Knowledge Discovery technology is emerging as a key technology for enterprises that wish to improve their data analysis, decision support activities, and the automatic extraction of knowledge from data.
The objective of the Third International Conference on Data Warehousing and Knowledge Discovery DaWaK was to bring together researchers and practitioners to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of association rules, mining temporal patterns, data mining techniques, collaborative filtering, Web mining, visualization, matchmaking, evelopment and maintenance of data warehouses, OLAP, and distributed data warehouses.
These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries, and the program committee finally selected 34 papers. Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume.
Important topics including information theory, decision tree, Nave Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples.
Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools.
Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.
Download Data Warehousing Introduction part 2 People part 3 Process part 4 Technology part 5 Maintenance evolution and trends part 6 On line analytical processing book written by S. The application of data warehousing and data mining techniques to computer security is an important emerging area, as information processing and internet accessibility costs decline and more and more organizations become vulnerable to cyber attacks. These security breaches include attacks on single computers, computer networks, wireless networks, databases, or authentication compromises.
This book describes data warehousing and data mining techniques that can be used to detect attacks. It is designed to be a useful handbook for practitioners and researchers in industry, and is also suitable as a text for advanced-level students in computer science. Do you enjoy completing puzzles? Perhaps one of the most challenging yet rewarding puzzles is delivering a successful data warehouse suitable for data mining and analytics. The Analytical Puzzle describes an unbiased, practical, and comprehensive approach to building a data warehouse which will lead to an increased level of business intelligence within your organization.
New technologies continuously impact this approach and therefore this book explains how to leverage big data, cloud computing, data warehouse appliances, data mining, predictive analytics, data visualization and mobile devices.
The 24 revised full papers and 8 short papers presented were carefully reviewed and selected from 89 submissions. The papers are organized in topical sections on modeling and ETL, query optimization and parallelism, spatial data warehouses and applications, text mining and OLAP, recommendation and prediction, data mining optimization and machine learning techniques, mining and processing data streams, clustering and data mining applications, social network and graph mining, and event sequence and Web mining.
Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data.
On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability.
However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. Author : Alex Berson,Stephen J. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over entries on theories, methodologies, functionalities, and applications.
Author : George M. Marakas Publisher: N. Using a balanced professional and conversational approach, it explores the basic concepts of data mining, warehousing, and visualization with an emphasis on both technical and managerial issues and the implication of these modern emerging technologies on those issues. Data mining and visualization exercises using an included fully-enabled, but time-limited version of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software give students hands-on experience with real-world applications.
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