by
Delisle, Marc.
Call Number
005.756 23
Publication Date
2012
Summary
This is a practical hands-on book with clear instructions and lot of code examples. It takes a simple approach, guiding you through different architectural topics using realistic sample projects.
Format:
Electronic Resources
Relevance:
0.1361
by
Krishnaswamy, Jayaram.
Call Number
005.7585 22
Publication Date
2010
Format:
Electronic Resources
Relevance:
0.1313
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by
Inmon, William H.
Call Number
005.74 22
Publication Date
2008
Summary
People have a hard time communicating, and also have a hard time finding business knowledge in the environment. With the sophistication of search technologies like Google, business people expect to be able to get their questions answered about the business just like you can do an internet search. The truth is, knowledge management is primitive today, and it is due to the fact that we have poor business metadata management. This book is about all the groundwork necessary for IT to really support the business properly. By providing not just data, but the context behind the data. For the IT professional, it will be tactically practical--very "how to" and a detailed approach to implementing best practices supporting knowledge management. And for the the IT or other manager who needs a guide for creating and justifying projects, it will help provide a strategic map. * First book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management. * Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, and filled with war stories, examples, and cases from current projects. * Very practical, includes a complete metadata acquisition methodology and project plan to guide readers every step of the way. * Includes sample unstructured metadata for use in self-testing and developing skills.
Format:
Electronic Resources
Relevance:
0.0953
by
George, Nathan, author.
Call Number
005.7 23
Publication Date
2021
Summary
The book provides a one-stop solution for getting into data science with Python and teaches how to extract insights from data.
Format:
Electronic Resources
Relevance:
0.0891
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