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Data Integration Hub Intro (Desirable Features (Multiple 'Right…
Data Integration Hub Intro
Benifit
Reduces number and complexity of interfaces
Easy to learn, design, maintain
Fosters reuse, standards, virtualization
Sacles and performs
Avoid Point-to-Point Hairball
Uncontrolled number of interfaces
Impossible to decipher and maintin
Reuse and standards are nonexistent
Data Integration Architecture
Simple, predictable patterns
Development standards
Collaborative processes
Unified system that can be controlled and optimized
Desirable Features
Multiple 'Right-Time" Speeds
Real time, near time, on demand, batch, micro batch
Support technologies that enable real time:
Service oriented interfaces, data federation, CDC, in-memory processing
True Real Time: Complex event processing (CEP) is now a DI discipline
Ideal for Streaming big data
Control
Data Access and movement
Data compliance: security, privacy, governance
Data Operation: scheduling, restart, QA, auditing, logging
Data Standards: via centralized development
Enforce Hub and Spoke
Support Publish and Subscribe Methods
How it works:
Certify
and
visualizer
data as it's published into Hub; So data is in a canonical form, ready for trusted reuse
Business friendly view of source data
Self service, data stewardship, exploration
Supports complex data flows
Multi directional :
Multiple sources or targets one-to-many
Multiple data mgt function
Data integration(ETL, federation, replication)
Quality: validation, standardization, dedupe
meta/master data, event processing, change data capture
Scale
Big data
High performance
Grid, cloud,MPP
In memory for pipeling
Avoid the Roach Motel Hub: Checks In but little checks out
Data integration architecture is simply the pattern made when servers relate through interfaces