Historically, the demands of independent business processes led to the development of applications with a focus on satisfying immediate functional or operational requirements. And although some historically developed applications continue to rely on batch processing windows, increased computational resources and speedier networks have raised expectations among application user communities for more immediate interactions and responses from their applications. Whether we are talking about data warehousing, pervasive business intelligence, master data management, supplementing a services-oriented architecture, or business continuity and recovery planning, there is a greater interdependence of applications and a corresponding need for repurposing of data, generally addressed using traditional Extraction/Transformation/Loading (ETL) techniques.
But while the rates of explosive data volume growth continue to accelerate, processing windows continue to get shorter. Meeting the need for rapid interaction means reducing data sharing latency so that the business applications will not stall while waiting for the right information to be delivered. There is clearly a growing need for what could be called “right-time data integration” – methods for timely sharing of data across the application landscape that reduce latency, have low impact to operational systems, and yet increase data coherence and consistency.
In this talk we consider three low risk yet proven and mature techniques for right-time data integration: Replication, change data capture and data federation.
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