Principle of Data warehousing


Book Description

"Principles of Data Warehousing" is an extensive and reputable book that explores the fundamental ideas, techniques, and industry best practices necessary for developing, overseeing, and refining data warehousing systems. This book is a must-have for anybody looking to learn more about data warehousing or improve their skills in the industry, since it is written by well-known specialists in the subject. The book commences by laying a robust groundwork through a comprehensive examination of the core principles and concepts of data warehousing. This enables readers to gain a clear knowledge of the objectives, advantages, and constituent elements of the system. Subsequently, the course delves into comprehensive subjects including data governance, analysis of dimensions, data modelling, ETL (Extract, Transform, Load) procedures, and data integration. Every chapter has been carefully designed to offer a combination of theoretical understanding and practical advice, thereby simplifying and rendering realistic intricate concepts. The text provides readers with practical exercises, examples that intersperse practical applications of the explored principles and facilitate experiential learning, thereby enhancing their comprehension. Furthermore, it addresses contemporary challenges including big data integration, cloud-based data warehousing, as well as real-time analytics, while "Principles of Data Warehousing" remains abreast of the most recent developments and trends in the region. The book empowers readers with the necessary knowledge and abilities to adeptly and confidently navigate the dynamic realm of data management by ensuring they remain updated on emergent technologies as well as methodologies. "Principles of Data Warehousing" is an essential resource for individuals embracing the art and science regarding data warehousing, including data architects, business analysts, database administrators, and those aspiring to become data professionals. This book equips readers with the ability to develop, execute, and enhance data warehousing solutions which generate value, understanding, and innovation for businesses of all sizes and in all sectors, through its extensive examination, pragmatic advice, and focus on fundamental principles.




Principles of Database Management


Book Description

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.




Data Mining and Data Warehousing


Book Description

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 Warehousing Fundamentals


Book Description

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.




Data Warehouse Design: Modern Principles and Methodologies


Book Description

Foreword by Mark Stephen LaRow, Vice President of Products, MicroStrategy "A unique and authoritative book that blends recent research developments with industry-level practices for researchers, students, and industry practitioners." Il-Yeol Song, Professor, College of Information Science and Technology, Drexel University




Principles of Data Integration


Book Description

Principles of Data Integration is the first comprehensive textbook of data integration, covering theoretical principles and implementation issues as well as current challenges raised by the semantic web and cloud computing. The book offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand. Readers will also learn how to build their own algorithms and implement their own data integration application. Written by three of the most respected experts in the field, this book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. This text is an ideal resource for database practitioners in industry, including data warehouse engineers, database system designers, data architects/enterprise architects, database researchers, statisticians, and data analysts; students in data analytics and knowledge discovery; and other data professionals working at the R&D and implementation levels. - Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand - Enables you to build your own algorithms and implement your own data integration applications




Data Warehouse Performance


Book Description

Reduce operating and maintenance costs while substantially improving the performance of new and existing data warehouses and data marts Data Warehouse Performance This book tells you what you need to know to design, build, and manage data warehouses and data marts for optimum performance. Written by an all-star team of data warehouse pioneers and innovators-including Bill Inmon, "the father of the data warehouse," and Ken Rudin, one of the leading experts on performance-the book describes the layers of a high-performance data warehouse environment and guides the reader through their implementation and management. It also supplies proven techniques for supercharging the performance of existing environments. Crucial topics covered include: * Mitigating the impact of dormant data on performance * Data cleansing and implementation techniques * Implementing platform components like data marts to support scalability * Database design, sizing, and optimization techniques, including star schema and indexing * Hardware assessment, selection, and sizing * The role of monitors in balancing workload and assessing performance * Creating a service management contract to meet user expectations




Data Mesh


Book Description

Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.




Mastering Data Warehouse Design


Book Description

A cutting-edge response to Ralph Kimball's challenge to thedata warehouse community that answers some tough questions aboutthe effectiveness of the relational approach to datawarehousing Written by one of the best-known exponents of the Bill Inmonapproach to data warehousing Addresses head-on the tough issues raised by Kimball andexplains how to choose the best modeling technique for solvingcommon data warehouse design problems Weighs the pros and cons of relational vs. dimensional modelingtechniques Focuses on tough modeling problems, including creating andmaintaining keys and modeling calendars, hierarchies, transactions,and data quality