Traditional data warehousing has long used batch jobs to move, load and transform data for decision making. But as data volumes rise and the velocity of business grows, more organizations are opting to move and process data in real-time or near real-time. Batch processing is giving way to mini-batches fueled by replication and change data capture as well as stream processing in which events are captured, processed, and analyzed as they happen.
Many companies today have a mix of batch, mini-batch, and stream-based processing. The questions is whether organizations should embrace streaming as the default mode of data acquisition? Several vendors are now pitching streaming-first architectures and extolling the benefits of processing data in real-time. This webinar will explore the pros and cons of a streaming-first architecture and examine industry trends in its adoption.
You Will Learn:
– What are the core components of a streaming architecture?
– What are the benefits and challenges of streaming data?
– How do you migrate to a streaming architecture?
– How does streaming affect the way you design applications and data pipelines?
– How does streaming support historical data and complex transformations?