Data architecture : a primer for the data scientist : big data, data warehouse and data vault /
Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems)....
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Amsterdam :
Elsevier,
[2014]
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| Subjects: | |
| Online Access: | CONNECT |
Table of Contents:
- Corporate data
- 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
- A brief history of big data
- What is big data?
- Parallel processing
- Unstructured data
- Contextualizing repetitive unstructured data
- Textual disambiguation
- Taxonomies
- A brief history of data warehouse
- Integrated corporate data
- Historical data
- Data marts
- What a data warehouse is not
- Introduction to data vault
- 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
- Metadata
- Data governance of structured data
- A brief history of data architecture
- Big data/existing systems interface
- The data warehouse/operational environment interface
- Data architecture : a high-level perspective
- Repetitive analytics : some basics
- Analyzing repetitive data
- Repetitive analysis
- Nonrepetitive data
- Mapping
- Analytics from nonrepetitive data
- Operational analytics
- Operational analytics
- Personal analytics
- A composite data architecture.
