http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (xv, 416 pages) : illustrations (chiefly color)
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.
1. Introduction to architecture 2. "Diagram of the world#x94;, end state architecture 3. Transformation and redundancy 4. Big Data 5. Siloed applications 6. Data vault 7. Data lake, ponds, landing zone 8. IoT, Edge computing 9. Operational environment 10. The evolution of data architecture 11. Repetitive data, the sandbox 12. Non-repetitive data, contextualization 13. Operational performance 14. Integration of data 15. Personal computing 16. Managing text, taxonomies 17. System of record 18. The intellectual roadmap -- data modelling, taxonomies, etc. 19. Business value across the architecture 20. Virtualization, streaming 21. The end of evolution
W.H. Inmon, Daniel Linstedt, Mary Levins.