Data architecture : a primer for the data scientist / W.H. Inmon, Daniel Linstedt, and Mary Levins.

Includes index.

An introduction to data architecture -- The data infrastructure -- The "great divide" -- Demographics of corporate data -- Corporate data analysis -- The life cycle of data: understanding data over time -- A brief history of data -- The end-state architecture-the "world map" -- Transformations in the end-state architecture -- A brief history of big data -- What is big data? -- Parallel processing -- Unstructured data -- Contextualizing repetitive unstructured data -- Textual disambiguation -- Taxonomies -- The siloed application environment -- Introduction to data vault 2.0 -- Introduction to data vault modeling -- Introduction to data vault architecture -- Introduction to data vault methodology -- Introduction to data vault implementation -- The operational environment: a short history -- The standard work unit -- Data modeling for the structured environment -- A brief history of data architecture -- Big data/existing system interface -- The data warehouse/operational environment -- Data architecture: a high-level perspective -- Repetitive analytics: some basics -- Analyzing repetitive data -- Repetitive analysis -- Nonrepetitive data -- Mapping -- Analytics from nonrepetitive data -- Operational analytics: response time -- Operational analytics -- Personal analytics -- Data models across the end-state architecture -- The system of record -- Business value and the end-state architecture -- Managing text -- An introduction to data visualizations.