Download or read book Data Warehousing Olap And Data Mining written by S. Nagabhushana and published by New Age International. This book was released on 2006 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Warehouses and OLAP written by Robert Wrembel and published by IGI Global. This book was released on 2007-01-01 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data warehouses and online analytical processing (OLAP) are emerging key technologies for enterprise decision support systems. They provide sophisticated technologies from data integration, data collection and retrieval, query optimization, and data analysis to advanced user interfaces. New research and technological achievements in the area of data warehousing are implemented in commercial database management systems, and organizations are developing data warehouse systems into their information system infrastructures. Data Warehouses and OLAP: Concepts, Architectures and Solutions covers a wide range of technical, technological, and research issues. It provides theoretical frameworks, presents challenges and their possible solutions, and examines the latest empirical research findings in the area. It is a resource of possible solutions and technologies that can be applied when designing, implementing, and deploying a data warehouse, and assists in the dissemination of knowledge in this field.
Download or read book Learn Data Warehousing in 24 Hours written by Alex Nordeen and published by Guru99. This book was released on 2020-09-15 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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?
Download or read book Data Warehousing Data Mining and OLAP written by Alex Berson and published by McGraw-Hill Companies. This book was released on 1997 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data Warehousing" is the nuts-and-bolts guide to designing a data management system using data warehousing, data mining, and online analytical processing (OLAP) and how successfully integrating these three technologies can give business a competitive edge.
Download or read book Data Warehouse and Data Mining written by Dr. Jugnesh Kumar and published by BPB Publications. This book was released on 2024-01-25 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unveiling insights, unleashing potential: Navigating the depths of data warehousing and mining for a data-driven tomorrow KEY FEATURES ● Explore concepts ranging from fundamentals to advanced techniques of data warehouses and data mining. ● Translate business questions into actionable strategies to make informed decisions. ● Gain practical implementation guidance for hands-on learning. DESCRIPTION Data warehouse and data mining are essential technologies in the field of data analysis and business intelligence. Data warehouse provides a centralized repository of structured data and facilitates data storage and retrieval. Data mining, on the other hand, utilizes various algorithms and techniques to extract valuable patterns, trends, and insights from large datasets. The book explains the ins and outs of data warehousing by discussing its principles, benefits, and components, differentiating it from traditional databases. The readers will explore warehouse architecture, learn to navigate OLTP and OLAP systems, grasping the crux of the difference between ROLAP and MOLAP. The book is designed to help you discover data mining secrets with techniques like classification and clustering. You will be able to advance your skills by handling multimedia, time series, and text, staying ahead in the evolving data mining landscape. By the end of this book, you will be equipped with the skills and knowledge to confidently translate business questions into actionable strategies, extracting valuable insights for informed decisions. WHAT YOU WILL LEARN ● Designing and building efficient data warehouses. ● Handling diverse data types for comprehensive insights. ● Mastering various data mining techniques. ● Translating business questions into mining strategies. ● Techniques for pattern discovery and knowledge extraction. WHO THIS BOOK IS FOR From aspiring data analysts, data professionals, IT managers, to business intelligence practitioners, this book caters to a diverse audience. TABLE OF CONTENTS 1. Introduction to Data Warehousing 2. Data Warehouse Process and Architecture 3. Data Warehouse Implementation 4. Data Mining Definition and Task 5. Data Mining Query Languages 6. Data Mining Techniques 7. Mining Complex Data Objects
Download or read book New Trends in Data Warehousing and Data Analysis written by Stanisław Kozielski and published by Springer Science & Business Media. This book was released on 2008-11-21 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.
Download or read book Data Warehousing written by Wolfgang Martin and published by . This book was released on 1998 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Warehousing OLAP and Data Mining written by Yao Ma and published by . This book was released on 1998 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book DATA MINING AND WAREHOUSING written by Khusboo Saxena/Sandeep Saxena/Akash Saxena and published by BPB Publications. This book was released on 2018-06-06 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Data Mining and Data Warehousing written by Parteek Bhatia and published by Cambridge University Press. This book was released on 2019-04-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book DATA WAREHOUSING written by C.S.R. PRABHU and published by PHI Learning Pvt. Ltd.. This book was released on 2008-08-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Third Edition of this well-received text analyses the fundamental concepts of data warehousing, data marts, and OLAP. The author discusses, in an easy-to-understand language, important topics such as data mining, how to build a data warehouse, and potential applications of data warehousing technology in government. Besides, the text compares and contrasts the currently available software tools used to design and develop data warehouses. While retaining the six existing case studies, it gives four new case studies: HARBOR, A Highly Available Data Warehouse A Typical Business Data Warehouse for a Trading Company Customer Data Warehouse for the World’s First and Largest Online Bank in the United Kingdom A German Supermarket EDEKA’s Data Warehouse The book, which is a blend of principles and real-life case studies, is intended as a text for students of B.Tech/M.Tech (Computer Science and Engineering), B.Tech/M.Tech (Information Technology), MBA, M.Sc. (Computer Science), M.Sc. (Information Technology), and MCA. It should also be of considerable utility and worth to software professionals and database practitioners.
Download or read book Data Warehousing Fundamentals written by Paulraj Ponniah and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geared to IT professionals eager to get into the all-importantfield of data warehousing, this book explores all topics needed bythose who design and implement data warehouses. Readers will learnabout planning requirements, architecture, infrastructure, datapreparation, information delivery, implementation, and maintenance.They'll also find a wealth of industry examples garnered from theauthor's 25 years of experience in designing and implementingdatabases and data warehouse applications for majorcorporations. Market: IT Professionals, Consultants.
Download or read book Data Warehousing Data Mining Olap written by Berson and published by Tata McGraw-Hill Education. This book was released on 2004-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Encyclopedia of Data Warehousing and Mining written by Wang, John and published by IGI Global. This book was released on 2005-06-30 with total page 1382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Data Warehousing and Analytics written by David Taniar and published by Springer Nature. This book was released on 2022-02-04 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook covers all central activities of data warehousing and analytics, including transformation, preparation, aggregation, integration, and analysis. It discusses the full spectrum of the journey of data from operational/transactional databases, to data warehouses and data analytics; as well as the role that data warehousing plays in the data processing lifecycle. It also explains in detail how data warehouses may be used by data engines, such as BI tools and analytics algorithms to produce reports, dashboards, patterns, and other useful information and knowledge. The book is divided into six parts, ranging from the basics of data warehouse design (Part I - Star Schema, Part II - Snowflake and Bridge Tables, Part III - Advanced Dimensions, and Part IV - Multi-Fact and Multi-Input), to more advanced data warehousing concepts (Part V - Data Warehousing and Evolution) and data analytics (Part VI - OLAP, BI, and Analytics). This textbook approaches data warehousing from the case study angle. Each chapter presents one or more case studies to thoroughly explain the concepts and has different levels of difficulty, hence learning is incremental. In addition, every chapter has also a section on further readings which give pointers and references to research papers related to the chapter. All these features make the book ideally suited for either introductory courses on data warehousing and data analytics, or even for self-studies by professionals. The book is accompanied by a web page that includes all the used datasets and codes as well as slides and solutions to exercises.
Download or read book Emerging Perspectives in Big Data Warehousing written by Taniar, David and published by IGI Global. This book was released on 2019-06-28 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of a big data warehouse appeared in order to store moving data objects and temporal data information. Moving objects are geometries that change their position and shape continuously over time. In order to support spatio-temporal data, a data model and associated query language is needed for supporting moving objects. Emerging Perspectives in Big Data Warehousing is an essential research publication that explores current innovative activities focusing on the integration between data warehousing and data mining with an emphasis on the applicability to real-world problems. Featuring a wide range of topics such as index structures, ontology, and user behavior, this book is ideally designed for IT consultants, researchers, professionals, computer scientists, academicians, and managers.
Download or read book Data warehouse data mining written by Roland Gabriel and published by W3l GmbH. This book was released on 2009 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Charakteristika dieses Buches: Umfassende Darstellung der Themenbereiche Data Warehousing und Data Mining . Den betrieblichen Alltag optimieren. Vermittlung der technischen Komponenten zur Informationsversorgung und Entscheidungsunterstützung. Alle konzeptionellen und technischen Grundlagen werden vorgestellt. Mit zahlreichen Beispielen aus einer durchgängigen Fallstudie. Analysedaten multidimensional modellieren und in einer geeigneten Architektur implementieren. Unter Einsatz leistungsfähiger Methoden zielführend Analysedaten auswerten. Themenschwerpunkte: Data Warehouse und OLAP, On-Line Analytical Processing, Modellierung multidimensionaler Datenstrukturen, Data Mining, CRISP-DM-Modell.