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Author : Parteek Bhatia
Publisher : Cambridge University Press
Page : 513 pages
File Size : 50,6 Mb
Release : 2019-06-27
Category : Computers
ISBN : 9781108727747
Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.
Author : Parteek Bhatia
Publisher : Cambridge University Press
Page : 128 pages
File Size : 52,9 Mb
Release : 2019-04-30
Category : Computers
ISBN : 9781108585859
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, Naïve 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.
Author : Anoop Singhal
Publisher : Springer Science & Business Media
Page : 166 pages
File Size : 41,9 Mb
Release : 2007-04-06
Category : Computers
ISBN : 9780387476537
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.
Author : Wang, John
Publisher : IGI Global
Page : 1382 pages
File Size : 42,7 Mb
Release : 2005-06-30
Category : Computers
ISBN : 9781591405597
Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.
Author : Khusboo Saxena/Sandeep Saxena/Akash Saxena
Publisher : BPB Publications
Page : 121 pages
File Size : 47,7 Mb
Release : 2018-06-06
Category : Computers
ISBN : 9789387284715
Description:The book has been written in such a way that the concepts are explained in detail, giving adequate emphasis on examples. To make clarity on the topic, diagrams are given extensively throughout the text. The book discusses design issues for phases of mining in substantial depth. The stress is more on problem solving.Various Comprehensive coverage of various aspects of Data Mining and Warehousing conceptsStrictly in accordance for the syllabus covered under B.E./B.Tech/MCASimple language, crystal clear approach, straight forward comprehensible presentationAdopting user friendly classroom lecture styleThe concepts are duly supported by sever examplesSyllabus coverage of three universities UPTU, RTU and RGPVTable Of Contents:Chapter 1 : Introduction To Data MiningChapter 2 : Concept DescriptionChapter 3 : Association Rule MiningChapter 4 : Classification and PredictionsChapter 5 : Cluster AnalysisChapter 6 : Introduction to Data WarehouseChapter 7 : OLAP TechnologyChapter 8 : Advance Topic On Data Mining and Warehousing
Author : Furtado, Pedro Nuno San-Banto
Publisher : IGI Global
Page : 364 pages
File Size : 53,5 Mb
Release : 2009-09-30
Category : Computers
ISBN : 9781605668178
"This book provides insight into the latest findings concerning data warehousing, data mining, and their applications in everyday human activities"--Provided by publisher.
Author : S. Nagabhushana
Publisher : New Age International
Page : 22 pages
File Size : 49,6 Mb
Release : 2006
Category : Data mining
ISBN : 9788122417647
This Book Is Mainly Intended For It Students And Professionals To Learn Or Implement Data Warehousing Technologies. It Experiences The Real-Time Environment And Promotes Planning, Managing, Designing, Implementing, Supporting, Maintaining And Analyzing Data Warehouse In Organizations And It Also Provides Various Mining Techniques As Well As Issues In Practical Use Of Data Mining Tools.The Book Is Designed For The Target Audience Such As Specialists, Trainers And It Users. It Does Not Assume Any Special Knowledge As Background. Understanding Of Computer Use, Databases And Statistics Will Be Helpful.
Author : David Taniar,Li Chen
Publisher : IGI Global
Page : 0 pages
File Size : 43,6 Mb
Release : 2011
Category : Computers
ISBN : 1609605373
"This book provides a comprehensive compilation of knowledge covering state-of-the-art developments and research, as well as current innovative activities in data warehousing and mining, focusing on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real world problems"--Provided by publisher.
Author : Zhengxin Chen
Publisher : CRC Press
Page : 256 pages
File Size : 53,5 Mb
Release : 2001-12-13
Category : Computers
ISBN : 9781420040616
Effective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in fact many of its advances have and will continue to come from the computer science arena. Intelligent Data Warehousing presents the state of the art in data warehousing research and practice from a perspective that integrates business applications and computer science. It brings the intelligent techniques associated with artificial intelligence (AI) to the entire process of data warehousing, including data preparation, storage, and mining. Part I provides an overview of the main ideas and fundamentals of data mining, artificial intelligence, business intelligence, and data warehousing. Part II presents core materials on data warehousing, and Part III explores data analysis and knowledge discovery in the data warehousing environment, including how to perform intelligent data analysis and the discovery of influential association patterns. Bridging the gap between theoretical research and business applications, this book summarizes the main ideas behind recent research developments rather than setting forth technical details, and it presents case studies that show the how-to's of implementing these ideas. The result is a practical, first-of-its-kind book that brings together scattered research, unites MIS with computer science, and melds intelligent techniques with data warehousing.
Author : Alex Nordeen
Publisher : Guru99
Page : 111 pages
File Size : 49,9 Mb
Release : 2020-09-15
Category : Computers
ISBN : 8210379456XXX
Unlike popular belief, Data Warehouse is not a single tool but a collection of software tools. A data warehouse will collect data from diverse sources into a single database. Using Business Intelligence tools, meaningful insights are drawn from this data. The best thing about “Learn Data Warehousing in 1 Day" is that it is small and can be completed in a day. With this e-book, you will be enough knowledge to contribute and participate in a Data warehouse implementation project. The book covers upcoming and promising technologies like Data Lakes, Data Mart, ELT (Extract Load Transform) amongst others. Following are detailed topics included in the book Table Of Content Chapter 1: What Is Data Warehouse? 1. What is Data Warehouse? 2. Types of Data Warehouse 3. Who needs Data warehouse? 4. Why We Need Data Warehouse? 5. Data Warehouse Tools Chapter 2: Data Warehouse Architecture 1. Characteristics of Data warehouse 2. Data Warehouse Architectures 3. Datawarehouse Components 4. Query Tools Chapter 3: ETL Process 1. What is ETL? 2. Why do you need ETL? 3. ETL Process 4. ETL tools Chapter 4: ETL Vs ELT 1. What is ETL? 2. Difference between ETL vs. ELT Chapter 5: Data Modeling 1. What is Data Modelling? 2. Types of Data Models 3. Characteristics of a physical data model Chapter 6: OLAP 1. What is Online Analytical Processing? 2. Types of OLAP systems 3. Advantages and Disadvantages of OLAP Chapter 7: Multidimensional Olap (MOLAP) 1. What is MOLAP? 2. MOLAP Architecture 3. MOLAP Tools Chapter 8: OLAP Vs OLTP 1. What is the meaning of OLAP? 2. What is the meaning of OLTP? 3. Difference between OLTP and OLAP Chapter 9: Dimensional Modeling 1. What is Dimensional Model? 2. Elements of Dimensional Data Model 3. Attributes 4. Difference between Dimension table vs. Fact table 5. Steps of Dimensional Modelling 6. Rules for Dimensional Modelling Chapter 10: Star and SnowFlake Schema 1. What is Multidimensional schemas? 2. What is a Star Schema? 3. What is a Snowflake Schema? 4. Difference between Start Schema and Snowflake Chapter 11: Data Mart 1. What is Data Mart? 2. Type of Data Mart 3. Steps in Implementing a Datamart Chapter 12: Data Mart Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Mart? 3. Differences between a Data Warehouse and a Data Mart Chapter 13: Data Lake 1. What is Data Lake? 2. Data Lake Architecture 3. Key Data Lake Concepts 4. Maturity stages of Data Lake Chapter 14: Data Lake Vs Data Warehouse 1. What is Data Warehouse? 2. What is Data Lake? 3. Key Difference between the Data Lake and Data Warehouse Chapter 15: What Is Business Intelligence? 1. What is Business Intelligence 2. Why is BI important? 3. How Business Intelligence systems are implemented? 4. Four types of BI users Chapter 16: Data Mining 1. What is Data Mining? 2. Types of Data 3. Data Mining Process 4. Modelling 5. Data Mining Techniques Chapter 17: Data Warehousing Vs Data Mining 1. What is Data warehouse? 2. What Is Data Mining? 3. Difference between Data mining and Data Warehousing?
Author : S. Prabhu,Na Vēṅkaṭēcan̲
Publisher : New Age International
Page : 11 pages
File Size : 49,8 Mb
Release : 2007-12
Category : Data mining
ISBN : 9788122419726
Data Mining is the process of analyzing large amount of data in search of previously undiscovered business patterns. Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. 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.
Author : Jiawei Han,Micheline Kamber,Jian Pei
Publisher : Elsevier
Page : 740 pages
File Size : 50,6 Mb
Release : 2011-06-09
Category : Computers
ISBN : 9780123814807
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Author : George M. Marakas
Publisher : Unknown
Page : 300 pages
File Size : 49,8 Mb
Release : 2003
Category : Business & Economics
ISBN : UOM:39015056230553
For undergraduate/graduate-level Data Mining or Data Warehousing courses in Information Systems or Operations Management Departments electives. Taking a multidisciplinary user/manager approach, this text looks at data warehousing technologies necessary to support the business processes of the twenty-first century. 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.
Author : Barbara Mento
Publisher : Association of Research Libr
Page : 84 pages
File Size : 54,5 Mb
Release : 2003
Category : Data mining
ISBN : UOM:39015052882167
"The goal of this survey was to determine the extent to which data mining technology is being used by ARL member institutions, researchers, libraries and and administrations. The survey also hoped to elicit ideas and opinions concerning the potential role of libraries in supporting data mining and data warehousing in research institutions. The first seven survey questions focus on data mining and data warehousing activities at the institutional level. The remaining questions explore the current library use of data mining technology and opportunities for future use. Since data warehouses are the foundation of data mining, several questions focused on current support and future plans for data warehousing. The survey was sent to 124 ARL member libraries. Sixty-five (52%) responded to the survey"--P. 9.
Author : S. Sumathi,S.N. Sivanandam
Publisher : Springer
Page : 828 pages
File Size : 55,8 Mb
Release : 2006-10-12
Category : Computers
ISBN : 9783540343516
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.