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Big data central data

Scenario ID

  • SC-BDH

Scenario Name

  • Big Data Hub

Characteristics

  • Central hub for collecting both batch information and transient information into a warehouse that is available for live services. Handles structured and unstructured data.

Description

  • Big data receives and organizes all types of data:
    • Batched in reference data
    • Event driven business data
    • Transient data from ‘event sniffing’, where the interface monitoring mechanism also sends updates to a big data hub
    • Unstructured data – for example emails
  • The role of Big Data is to be able to support these large and constant streams of data and still keep data organized, transformed and sorted in a useful way for real-time systems to have direct access to the data-collection via live services. It combines all four basic patterns.

R ecommendations

  • Consider a combination of an ETL tool, + big central data hub (S2SMSG + S2SETL + S2SBDH), where data is collected (and can be combined and re-used) on the way between source and target: S2SBDH. S2SBDH should stimulate re-use of data-replication interfaces using event driven replication - SC-EDR

Example

  • None

Pattern Reference