rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data architecture
    sub title: a primer for the data scientist
  name:
    name part: Inmon, William H.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Linst, Daniel
    role:
      role term: author.
  name:
    name part: Levins, Mary
    role:
      role term: author.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2019
    edition: Second edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xv, 416 pages) : illustrations (chiefly color)
  abstract: 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.
  table of contents: 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
  note: W.H. Inmon, Daniel Linstedt, Mary Levins.
  note: Includes index.
  subject:
    topic: Data warehousing
  subject:
    topic: Big data
  subject:
    topic: Electronic data processing
  subject:
    topic: Information retrieval
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Entrepôts de données (Informatique)
  subject:
    topic: Données volumineuses
  subject:
    topic: Recherche de l'information
  subject:
    topic: information retrieval
  subject:
    topic: COMPUTERS
    topic: Data Modeling & Design
  subject:
    topic: Information retrieval
  subject:
    topic: Electronic data processing
  subject:
    topic: Big data
  subject:
    topic: Data warehousing
  subject:
    topic: Data-Warehouse-Konzept
  subject:
    topic: Big Data
  subject:
    topic: Softwarearchitektur
  classification: QA76.9.D37 I4575 2019
  classification: QA76.9.D37 .I56 2019
  classification: 005.745
  identifier: 9780128169179
  identifier: 0128169176
  identifier: 9780128169162
  identifier: 0128169168
  identifier: 2018966172
  identifier: 9780128169179 Ingram Content Group
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: N$T
    record creation date: 190502
    record change date: 20260327162833.2
    record identifier: in00005764920
    language of cataloging:
      language term: eng