Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Автор: Dan Linstedt Название: Building a Scalable Data Warehouse with Data Vault 2.0 ISBN: 0128025107 ISBN-13(EAN): 9780128025109 Издательство: Elsevier Science Рейтинг: Цена: 9262.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
TheData Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures.
"Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss:
How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes.
Important data warehouse technologies and practices.
Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.
Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast
Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse
Demystifies data vault modeling with beginning, intermediate, and advanced techniques
Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0
Автор: Foster Provost Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking ISBN: 1449361323 ISBN-13(EAN): 9781449361327 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть (1 шт.) Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.
Автор: Kunigk Jan, George Lars, Wilkinson Paul Название: Architecting Modern Data Platforms2 ISBN: 149196927X ISBN-13(EAN): 9781491969274 Издательство: Wiley Рейтинг: Цена: 11403.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects.
Автор: Brown Meta S. Название: Data Mining for Dummies ISBN: 1118893174 ISBN-13(EAN): 9781118893173 Издательство: Wiley Рейтинг: Цена: 5067.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.
Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you ll understand how Kafka works and how it s designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure, tune, and monitor them; write rock-solid applications that use Kafka; and build scalable stream-processing applications.Learn how Kafka compares to other queues, and where it fits in the big data ecosystemDive into Kafka s internal designPick up best practices for developing applications that use KafkaUnderstand the best way to deploy Kafka in production monitoring, tuning, and maintenance tasksLearn how to secure a Kafka clusterGet detailed use-cases"
Автор: Chambers Bill, Zaharia Matei Название: Spark: The Definitive Guide: Big Data Processing Made Simple ISBN: 1491912219 ISBN-13(EAN): 9781491912218 Издательство: Wiley Рейтинг: Цена: 8869.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Ladley John Название: Data Governance ISBN: 012815831X ISBN-13(EAN): 9780128158319 Издательство: Elsevier Science Рейтинг: Цена: 7915.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity.
Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program.
Incorporates industry changes, lessons learned and new approaches
Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations
Includes new case studies which detail real-world situations
Explores all of the capabilities an organization must adopt to become data driven
Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional
Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities
Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy
Provides up to 75% brand-new content compared to the first edition
Название: Data mining with decision trees: theory and applications ISBN: 9812771719 ISBN-13(EAN): 9789812771711 Издательство: World Scientific Publishing Рейтинг: Цена: 17424.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. Dedicated to the field of decision trees in data mining, this book covers various aspects of this technique.
Описание: Highlights the pitfalls of data analysis and emphasizes the importance of using the appropriate metrics before making key decisions. Big data is often touted as the key to understanding almost every aspect of contemporary life. This critique of "information hubris" shows that even more important than data is finding the right metrics to evaluate it. The author, an expert in environmental design and city planning, examines the many ways in which we measure ourselves and our world. He dissects the metrics we apply to health, worker productivity, our children's education, the quality of our environment, the effectiveness of leaders, the dynamics of the economy, and the overall well-being of the planet. Among the areas where the wrong metrics have led to poor outcomes, he cites the fee-for-service model of health care, corporate cultures that emphasize time spent on the job while overlooking key productivity measures, overreliance on standardized testing in education to the detriment of authentic learning, and a blinkered focus on carbon emissions, which underestimates the impact of industrial damage to our natural world. He also examines various communities and systems that have achieved better outcomes by adjusting the ways in which they measure data. The best results are attained by those that have learned not only what to measure and how to measure it, but what it all means. By highlighting the pitfalls inherent in data analysis, this illuminating book reminds us that not everything that can be counted really counts.
Описание: The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations.
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