Semantic Modeling for Data : Avoiding Pitfalls and Breaking Dilemmas
Book Details
Format
Paperback / Softback
ISBN-10
1492054275
ISBN-13
9781492054276
Publisher
O'Reilly Media
Imprint
O'Reilly Media
Country of Manufacture
US
Country of Publication
GB
Publication Date
Sep 4th, 2020
Print length
306 Pages
Weight
588 grams
Dimensions
19.10 x 23.40 x 2.10 cms
Product Classification:
Semantics, discourse analysis, stylisticsSemantics & pragmaticsInformation theoryDigital and Information technology: general topicsInformation technology: general issuesData miningComputer architecture & logic designComputer architecture and logic designNatural language & machine translationNatural language and machine translation
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In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You’ll learn how to master this craft to increase the usability and value of your data and applications.
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to extract business gold—but you still fail. The reason? Bad data semantics. In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You’ll learn how to master this craft to increase the usability and value of your data and applications. You’ll also explore the pitfalls to avoid and dilemmas to overcome for building high-quality and valuable semantic representations of data. Understand the fundamental concepts, phenomena, and processes related to semantic data modelingExamine the quirks and challenges of semantic data modeling and learn how to effectively leverage the available frameworks and toolsAvoid mistakes and bad practices that can undermine your efforts to create good data modelsLearn about model development dilemmas, including representation, expressiveness and content, development, and governanceOrganize and execute semantic data initiatives in your organization, tackling technical, strategic, and organizational challenges
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