Edition |
Second edition. |
Description |
1 online resource (xv, 416 pages) : illustrations (chiefly color) |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
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text file |
Note |
Includes index. |
Summary |
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. |
Note |
Copyright ©: Elsevier Science & Technology 2019 |
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Description based on online resource; title from digital title page (viewed on June 20, 2023). |
Contents |
1. Introduction to architecture<br>2. "Diagram of the world#x94;, end state architecture<br>3. Transformation and redundancy<br>4. Big Data<br>5. Siloed applications<br>6. Data vault<br>7. Data lake, ponds, landing zone<br>8. IoT, Edge computing <br>9. Operational environment<br>10. The evolution of data architecture <br>11. Repetitive data, the sandbox <br>12. Non-repetitive data, contextualization <br>13. Operational performance <br>14. Integration of data <br>15. Personal computing <br>16. Managing text, taxonomies <br>17. System of record <br>18. The intellectual roadmap -- data modelling, taxonomies, etc. <br>19. Business value across the architecture <br>20. Virtualization, streaming <br>21. The end of evolution |
Subject |
Data warehousing.
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Big data.
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Electronic data processing.
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Information retrieval.
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Information Storage and Retrieval |
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Entrepôts de données (Informatique)
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Données volumineuses.
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Recherche de l'information.
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information retrieval.
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COMPUTERS -- Data Modeling & Design.
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Information retrieval
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Electronic data processing
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Big data
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Data warehousing
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Data-Warehouse-Konzept
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Big Data
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Softwarearchitektur
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Genre/Form |
Electronic books.
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Electronic books.
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Added Author |
Linst, Daniel, author.
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Levins, Mary, author.
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ISBN |
9780128169179 electronic book |
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0128169176 electronic book |
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9780128169162 paperback |
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0128169168 paperback |
Standard No. |
C20180016667 |
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9780128169179 |
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(WaSeSS)ssj0002571099 |
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AU@ 000065334998 |
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AU@ 000066136121 |
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AU@ 000066230707 |
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AU@ 000068128112 |
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UKMGB 019391665 |
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