Latency

Latency in the context of business intelligence and data analytics refers to the time delay between when data is captured and when it is available for analysis or action. Think of it like the lag between sending a text message and the time it takes for your friend to receive it. In a business setting, lower latency means that the data is fresher and decisions based on that data can be made more quickly.

For companies that rely on real-time data analysis, such as financial institutions that process stock trades or online retailers managing inventory, latency can be critical. High latency can mean losing out on important opportunities or failing to catch issues before they escalate. It’s like being a step behind in a fast-paced dance; timing is everything.

Businesses strive to reduce latency as much as possible to ensure that they are making decisions based on the most current information available. This can involve upgrading technology or optimizing data processes. In an age where speed can be a competitive advantage, understanding and minimizing latency ensures that businesses stay agile and responsive to rapidly changing conditions.