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This book is structured to guide you through the essential concepts and techniques of Data Warehousing and Data Mining. It begins with foundational topics and progressively delves into more complex areas, ensuring that readers develop a robust understanding of the subject matter. Practical examples and case studies are provided to illustrate how these concepts are applied in real-world scenarios, helping to bridge the gap between theory and practice. Our goal with this book is to equip you with the knowledge and skills necessary to harness the power of data within your organization. Whether you are embarking on a new project or looking to enhance existing systems, this book will serve as a valuable resource on your journey.
It is with great pleasure that we present IGNOU MCA Previous Years Unsolved Papers - Part 2, a comprehensive collection of previous years' question papers, meticulously curated to support students pursuing a Master of Computer Applications (MCA) degree from the Indira Gandhi National Open University (IGNOU). This book is designed to serve as a valuable resource for students preparing for their MCA exams, helping them not only to understand the examination pattern but also to enhance their problem-solving skills and self-assessment abilities. The IGNOU MCA program is one of the most reputed distance learning programs in India, and it requires students to possess both theoretical knowledge and practical skills across various subjects related to computer science, software development, and application management. Given the vastness of the syllabus and the technical rigor of the program, students often seek additional support material to solidify their understanding of key concepts and prepare effectively for the exams. This book is intended to fill that gap by providing a comprehensive set of unsolved question papers from previous years.
It is with great pleasure that we present IGNOU MCA Previous Years Unsolved Papers – All in One, a comprehensive collection of previous years' question papers, meticulously curated to support students pursuing a Master of Computer Applications (MCA) degree from the Indira Gandhi National Open University (IGNOU). This book is designed to serve as a valuable resource for students preparing for their MCA exams, helping them not only to understand the examination pattern but also to enhance their problem-solving skills and self-assessment abilities. The IGNOU MCA program is one of the most reputed distance learning programs in India, and it requires students to possess both theoretical knowledge and practical skills across various subjects related to computer science, software development, and application management. Given the vastness of the syllabus and the technical rigor of the program, students often seek additional support material to solidify their understanding of key concepts and prepare effectively for the exams. This book is intended to fill that gap by providing a comprehensive set of unsolved question papers from previous years.
The purpose of this book is to provide students with a practical tool to prepare for their exams more effectively. IGNOU’s open and distance learning model demands a high level of self-discipline and independent study. As such, practicing with previous years' papers can significantly enhance students' understanding of key concepts and improve their performance in exams. By solving these papers, students can evaluate their readiness, identify areas that require more focus, and become comfortable with the exam pattern and question formats. The unsolved nature of the papers is particularly beneficial, as it challenges students to think critically and develop their own solutions. This approach promotes active learning and reinforces theoretical knowledge through practical application.
This book, IGNOU Database Management Systems Previous Years Unsolved Papers (MCS-207), is a thoughtfully compiled collection of unsolved question papers from previous years. It is designed to serve as an indispensable resource for students preparing for their exams in DBMS. The primary aim of this book is to equip students with a comprehensive tool to self-assess their understanding, pinpoint areas that require further study, and enhance their problem-solving capabilities.
The Book has been carefully curated to serve as an essential resource for students enrolled in the Post Graduate Diploma in Computer Applications (PGDCA) program at IGNOU. This book is a comprehensive compilation of previous years' theory papers for all Semester 2 subjects, designed to offer students a practical and thorough preparation tool for their exams.
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.
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
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
The International Encyclopedia of Information and Library Science was published to widespread acclaim in 1996, and has become the major reference work in the field. This eagerly awaited new edition has been fully revised and updated to take full account of the many and radical changes which have taken place since the Encyclopedia was originally conceived. With nearly 600 entries, written by a global team of over 150 contributors, the subject matter ranges from mobile library services provided by camel and donkey transport to search engines, portals and the World Wide Web. The new edition retains the successful structure of the first with an alphabetical organization providing the basic framework of a coherent collection of connected entries. Conceptual entries explore and explicate all the major issues, theories and activities in information and library science, such as the economics of information and information management. A wholly new entry on information systems, and enhanced entries on the information professions and the information society, are key features of this new edition. Topical entries deal with more specific subjects, such as collections management and information services for ethnic minorities. New or completely revised entries include a group of entries on information law, and a collection of entries on the Internet and the World Wide Web.