With more enterprises adopting cloud and ingesting data from multiple private and public sources, I have seen an increase in the need for addressing a classification scheme for data availability.
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All articles filed in data integration
Areas of Data Responsibility
I tend to rely on a notion called Areas of Responsibility when I need to architect a data focused solution.
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MDM Patterns
There are a number of architectural approaches and patterns to provision a quality single version of the truth with respect to key business entities and reference entities.
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Data Stream Engines
The Data Stream Capture Engine tends to be a distributed engine that efficiently captures, aggregates, and ingests large amounts of streamed data such as log data
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Data Replication & Synchronization
Replication & Synchronization enables the creation and maintenance of one or more synchronized standby data stores that protect data from failures, disasters, errors, and corruptions. It can address both high availability (HA) and disaster recovery (DR) requirements.
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Data Ingestion Patterns
Point to Point and Hub and Spoke ingestion patterns are the mostly used ingestion patterns.
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Data Ingestion
The need and timeliness of data should be taken into account when deciding which ingestion mechanism to employ.
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Data Acquisition
There is no one way to acquire data and it is up to the architect to decide which data acquisition technique(s) meets their requirements
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An Enterprise Architect's Musings 