Head of Developer Education, Developer Relations
Data generation is the first phase of the data engineering lifecycle, where data originates from real-world events: clicks, purchases, sensor readings, and system logs. Those events happen in real time, but access to them is often batched, because systems sync on a schedule or connectivity is limited. The answer is to build event-driven systems that assume data arrives continuously. When constraints force you to work with batches, process each batch the moment it lands, so the pipeline keeps working in real time as the constraints are removed.
You rarely control when data is generated, how it's formatted, or when it becomes available. Some data is available the instant it's created, such as user interactions and application logs. Other data is generated in real time but reaches you later, such as smartwatch, glucose monitor, and wind turbine readings. Streams get broken by constraints you can't control and by delays you add yourself. You can't always fix the first, but you can avoid the second.
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