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Data architecture : a primer for the data scientist /

Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault, Second Edition, addresses how Big Data fits within the existing information infrastructure and data warehousing systems. This is an essential topic as researchers and engineers increasingly need to deal with...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Inmon, William H. (Autor), Linst, Daniel (Autor), Levins, Mary (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London, United Kingdom ; San Diego, CA : Academic Press, [2019]
Edición:Second edition.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Inmon, William H.,  |e author. 
245 1 0 |a Data architecture :  |b a primer for the data scientist /  |c W.H. Inmon, Daniel Linstedt, Mary Levins. 
250 |a Second edition. 
264 1 |a London, United Kingdom ;  |a San Diego, CA :  |b Academic Press,  |c [2019] 
300 |a 1 online resource (xv, 416 pages) :  |b illustrations (chiefly color) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
500 |a Includes index. 
520 |a Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault, Second Edition, addresses how Big Data fits within the existing information infrastructure and data warehousing systems. This is an essential topic as researchers and engineers increasingly need to deal with large and complex sets of data. Until data is gathered and placed into an existing framework or architecture, it cannot be used to its full potential. Drawing upon years of practical experience and using numerous examples and case studies from across industries, the authors explain where Big Data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. 
542 |f Copyright &#169: Elsevier Science & Technology  |g 2019 
588 |a Description based on online resource; title from digital title page (viewed on June 20, 2023). 
650 0 |a Data warehousing. 
650 0 |a Big data. 
650 0 |a Electronic data processing. 
650 0 |a Information retrieval. 
650 2 |a Information Storage and Retrieval  |0 (DNLM)D016247 
650 6 |a Entrep�ots de donn�ees (Informatique)  |0 (CaQQLa)201-0300302 
650 6 |a Donn�ees volumineuses.  |0 (CaQQLa)000284673 
650 6 |a Recherche de l'information.  |0 (CaQQLa)201-0013918 
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650 7 |a COMPUTERS  |x Data Modeling & Design.  |2 bisacsh 
650 7 |a Information retrieval  |2 fast  |0 (OCoLC)fst00972619 
650 7 |a Electronic data processing  |2 fast  |0 (OCoLC)fst00906956 
650 7 |a Big data  |2 fast  |0 (OCoLC)fst01892965 
650 7 |a Data warehousing  |2 fast  |0 (OCoLC)fst00888026 
700 1 |a Linst, Daniel,  |e author. 
700 1 |a Levins, Mary,  |e author. 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128169162  |z Texto completo