Автор: Martin Kleppmann Название: Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems ISBN: 1449373321 ISBN-13(EAN): 9781449373320 Издательство: Wiley Рейтинг: Цена: 50680.00 T Наличие на складе: Заказано в издательстве. 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: 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: 42230.00 T Наличие на складе: Есть 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: Dan Linstedt Название: Building a Scalable Data Warehouse with Data Vault 2.0 ISBN: 0128025107 ISBN-13(EAN): 9780128025109 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T 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: Gorelik Alex Название: The Enterprise Big Data Lake: Delivering on the Promise of Hadoop and Data Science in the Enterprise ISBN: 1491931558 ISBN-13(EAN): 9781491931554 Издательство: Wiley Рейтинг: Цена: 67570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Mitchell Ryan Название: Web Scraping with Python: Collecting More Data from the Modern Web ISBN: 1491985577 ISBN-13(EAN): 9781491985571 Издательство: Wiley Рейтинг: Цена: 42230.00 T Наличие на складе: Поставка под заказ. Описание: The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web.
Автор: Malaska Ted, Seidman Jonathan Название: Foundations for Architecting Data Solutions: Managing Successful Data Projects ISBN: 1492038741 ISBN-13(EAN): 9781492038740 Издательство: Wiley Рейтинг: Цена: 47510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Big Data Solution Architecture provides everyone from CIOs and COOs to lead architects and lead developers with the fundamental concepts of big data development. Authors Ted Malaska and Jonathan Seidman guide you through all the major components necessary to start, architect, and develop successful big data projects.
Автор: Scholl Boris, Swanson Trent, Jausovec Peter Название: Cloud Native: Containers, Functions, Data, and Kubernetes: How to Build a Blueprint for Next-Generation Applications ISBN: 1492053821 ISBN-13(EAN): 9781492053828 Издательство: Wiley Рейтинг: Цена: 55960.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Learning about distributed systems, becoming familiar with technologies such as containers and functions, and knowing how to put everything together can be daunting. With this practical guide, you`ll get up to speed on patterns for building cloud native applications and best practices for common tasks such as messaging, eventing, and DevOps.
Автор: Schryvers Peter Название: Bad Data: Why We Measure the Wrong Things and Often Miss the Metrics That Matter ISBN: 1633885909 ISBN-13(EAN): 9781633885905 Издательство: NBN International Рейтинг: Цена: 26740.00 T Наличие на складе: Нет в наличии. 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.
Автор: Brown Meta S. Название: Data Mining for Dummies ISBN: 1118893174 ISBN-13(EAN): 9781118893173 Издательство: Wiley Рейтинг: Цена: 33780.00 T 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.
Автор: Grolemund Garrett, Wickham Hadley Название: R for Data Science ISBN: 1491910399 ISBN-13(EAN): 9781491910399 Издательство: Wiley Рейтинг: Цена: 46450.00 T Наличие на складе: Невозможна поставка. Описание: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun.
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
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"
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