Continuous Availability – Using Data Federation and Change Data Capture to Manage Information Synchrony
The organically grown application landscape is rife with independent business processes, potentially working at cross-purposes. Aligning functional departmental systems with an enterprise information management strategy exposes opportunities for data sharing and information reuse, as well as improved collaboration reliant on a coherent centralized enterprise information asset. However, despite the approaches used for data extraction and data warehouse population, real time operational activities continue to create, modify, or retire data, leading to increasing inconsistency between data warehouse refreshes.
Satisfying the immediate timeliness and currency requirements of dynamic operational business intelligence requires a more sophisticated approach to information synchronization. In this talk, we look at the drivers for data coherence, defining data synchronization requirements, and technical approaches that minimize the latency of coherent updates that provide high throughput, speed response time, yet impose limited impact of source systems, network bandwidth requirements, and target systems. Through incorporation of external (transient) data feeds that are not persistent, along with techniques such as change data capture (CDC), replication, and data federation, one can rapidly capture source data changes and deliver those changes to target systems. These techniques are the first component of dynamic operational BI, whether they support synchronizing data warehouses with operational systems or supplying analytics to detect and respond to emergent opportunities or risks.
You will learn:
- Considerations for data synchrony
- Concepts of data federation
- How change data capture streamlines data warehousing