
Sách Semantic Modeling for Data Avoiding Pitfalls and Breaking Dilemmas (sách keo gáy, bìa mềm)
Categories:Computers - Computer Science
Year:2020
Edition:1
Language:english
Pages:329
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 modeling
*
Examine the quirks and challenges of semantic data modeling and learn
how to effectively leverage the available frameworks and tools
* Avoid mistakes and bad practices that can undermine your efforts to create good data models
* Learn about model development dilemmas, including representation, expressiveness and content, development, and governance
*
Organize and execute semantic data initiatives in your organization,
tackling technical, strategic, and organizational challenges