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of things. Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data;
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into an existing framework or architecture it can't be used to its full potential. Data Architecture a Primer for the Data Scientist addresses;
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, technical skills, experience, and how the Data Scientist connects with other people. Be a Data Scientist for a day, examining the problems you may;
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developer, data architect, or a data scientist looking for information on how to integrate the Big Data stack architecture and how to choose the;
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warehousing, and warehouse design. This text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea;
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, you'll learn how to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the;
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This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The;
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This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The;
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many of these organizations can actually get the data back out in a useable form? Very few can turn the data lake into an information gold mine;
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Data Modeling for Agile Data Warehouse using Data Vault Modeling Approach. Includes Enterprise Data Warehouse Architecture. This is a;
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Policy-based data management enables the creation of community-specific collections. Every collection is created for a purpose. The purpose;
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scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into;
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A practical guide to implementing your enterprise data lake using Lambda Architecture as the base About This Book * Build a full;
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If you are a data scientist of any level, beginners included, and interested in cleaning up your data, this is the book for you! Experience;
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Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software;
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DW 2.0: The Architecture for the Next Generation of Data Warehousing is the first book on the new generation of data warehouse;
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inspired by the work of these authors. Their first book laid the groundwork for understanding how to evolve the architecture of a software;
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architecture framework * Roadmap to introduce big data as a service for potential clients * Presents a thorough description of each component in the;
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From the author of the bestsellers, Data Scientist and Julia for Data Science, this book covers four foundational areas of data science;
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This primer on data mining provides an introduction to the principles and techniques for extracting information from a business-minded;
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, Cassandra, and Kafka-in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus;
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In the fast moving world of the fourth industrial revolution not everyone needs to be a data scientist but everyone should be data literate;
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In the fast moving world of the fourth industrial revolution not everyone needs to be a data scientist but everyone should be data literate;
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Jump-start your career as a data scientist-learn to develop datasets for exploration, analysis, and machine learning SQL for Data;
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knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts;
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