Real-time data has the potential to provide significant value to businesses. However, it also comes with an expiration date. If this data is not utilized within a certain timeframe, its value is lost, and the corresponding decision or action is not taken. Such data is continuously generated and delivered rapidly, making it known as streaming data.
Siloed data systems that collect, store, and process data in batches can slow down data scientists and engineers who require quick access to operationalize data across the organization. Batch processing is particularly challenging when reducing latency and delivering powerful computing in real-time. This back-and-forth process between systems can leave companies one step behind their customers at every turn.