Data Warehousing And Data Mining
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Data Warehousing And Data Mining
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Author : Dr. M.Saranya
language : en
Publisher: True Dreamster Press
Release Date : 2024-05-15
Data Warehousing And Data Mining written by Dr. M.Saranya and has been published by True Dreamster Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Databases today can range in size into the terabytes — more than 1,000,000,000,000 bytes of data. Within these masses of data lies hidden information of strategic importance. Innovative organizations worldwide are already using data mining to locate and appeal to higher-value customers, reconfigure their product offerings to increase sales and minimize losses due to error or fraud. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. THE DATA MINING PROCESS, collecting, exploring, and selecting the right data is critically important. However, data description alone cannot provide an action plan.
Data Warehousing And Mining
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Author : ITLESL
language : en
Publisher: Pearson Education India
Release Date : 2012
Data Warehousing And Mining written by ITLESL and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Data Warehousing and Data Mining is presented in a question-and-answer format following the examination pattern and covers all key topics in the syllabus. The book is designed to make learning fast and effective and is precise, up-to-date and will help students excel in their examinations. The book is part of the Express Learning is a series of books designed as quick reference guides to important undergraduate courses. The organized and accessible format of these books allows students to learn important concepts in an easy-to-understand, question-and-answer format. These portable learning tools have been designed as one-stop references for students to understand and master the subjects by themselves.
Intelligent Data Warehousing
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Author : Zhengxin Chen
language : en
Publisher: CRC Press
Release Date : 2001-12-13
Intelligent Data Warehousing written by Zhengxin Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-12-13 with Computers categories.
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.
Data Mining And Warehousing
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Author : S. Prabhu
language : en
Publisher: New Age International
Release Date : 2007
Data Mining And Warehousing written by S. Prabhu and has been published by New Age International this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
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.
Data Warehousing And Data Mining
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Author : Dr. N. Madhusudhana Reddy, Dr. Saritha Anchuri, Dr. B. Ramakantha Reddy, Dr. Rajesh Kumar Maurya
language : en
Publisher: BR Publications
Release Date : 2025-12-18
Data Warehousing And Data Mining written by Dr. N. Madhusudhana Reddy, Dr. Saritha Anchuri, Dr. B. Ramakantha Reddy, Dr. Rajesh Kumar Maurya and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-18 with Computers categories.
Data Warehousing and Data Mining focuses on storing, managing, and analyzing large volumes of data for decision making. Data warehousing concepts include data integration, ETL processes, and multidimensional data models. It explains OLAP operations for efficient data analysis. Data mining techniques such as classification, clustering, and association rule mining are introduced. Statistical and machine learning methods support pattern discovery. Data preprocessing improves data quality and reliability. The subject highlights applications in business intelligence and analytics. Issues related to scalability, privacy, and security are discussed. Overall, it enables organizations to extract valuable insights from complex datasets.
Data Mining Concepts And Techniques
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Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2011-06-09
Data Mining Concepts And Techniques written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-09 with Computers categories.
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
Data Warehousing And Mining Concepts Methodologies Tools And Applications
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2008-05-31
Data Warehousing And Mining Concepts Methodologies Tools And Applications written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-31 with Technology & Engineering categories.
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. 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.
Learn Data Warehousing In 24 Hours
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Author : Alex Nordeen
language : en
Publisher: Guru99
Release Date : 2020-09-15
Learn Data Warehousing In 24 Hours written by Alex Nordeen and has been published by Guru99 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-15 with Computers categories.
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?
Data Mining And Data Warehousing
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Author : Barbara Mento
language : en
Publisher: Association of Research Libr
Release Date : 2003
Data Mining And Data Warehousing written by Barbara Mento and has been published by Association of Research Libr this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Data mining categories.
"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.
Data Mining Data Warehousing And Client Server Databases
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Author : Brian Siu
language : en
Publisher: Springer
Release Date : 1997-12
Data Mining Data Warehousing And Client Server Databases written by Brian Siu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-12 with Computers categories.
The 8th International Database Workshop, organized by the Hong Kong Computer Society and held in Hong Kong in July 1997, dedicated its theme to Data Mining, Data Warehouse and Client/Server Databases with separate focuses on the Academic and the Industrial Streams. It brought together database practitioners, researchers and vendors to share and explore their methodologies and experiences of advance database systems. These proceedings contain 22 of the selected papers received for the section on the Industrial Stream, written by database vendors and consultants from 14 countries around the world. It will serve as a useful and practical technology reference book on the latest findings in the field.