Imagine a bustling city with millions of people going about their daily lives. Now, picture a network of interconnected roads, each representing a data point, capturing the pulse of the city in real-time. This is the essence of data lakes and data warehouses, where vast amounts of information flow in and out, shaping the decisions that drive businesses forward. However, to harness the power of these architectures, real-time analytics is essential.

How much of the data you collect is actually getting analyzed? Most organizations are focused on trying not to drown in the seas of data generated daily. A small subset gets analyzed, but the rest usually gets dumped into a bucket or blob storage. “Oh, we’ll get back to it,” thinks every well-intentioned analyst as they watch data streams get sent away, never to be seen again.