In the context of operational analytics, businesses are faced with an important architectural decision between batch and event-driven data systems. Batch systems involve scheduled data upkeep, where data is synced on a set schedule to keep a resulting dataset up-to-date. In contrast, event-driven systems maintain a stream of events that occur over time, without updating historical data. The choice between the two ultimately depends on factors such as the team within the organization, the desire to update historical data, and business use cases. While batch systems are often built on top of common data tools, event orchestration occurs client-side on a website, requiring more expertise in engineering technology. Considerations include the need for continuous syncing, the ability to trigger actions based on events, and the ease of updating historical data. Ultimately, businesses should prioritize stakeholder needs and consider how their stakeholders will use the data when making this decision.