Data latency refers to the delay between sending a data request and receiving the response, which can significantly impact user retention and engagement. Even small delays of over 5.7 seconds can cause conversion rates to drop below 0.6%. Data timeliness is vital for businesses, especially in finance, healthcare, and e-commerce, as it ensures that information is current and relevant for accurate decision-making. Minimizing data latency requires understanding its causes, including network latency, processing delays, hardware limitations, and software and algorithms. Best practices to minimize data latency include optimizing network infrastructure, improving processing speed, upgrading hardware, adopting real-time data processing technologies, and utilizing compression techniques. By implementing these strategies, businesses can achieve their goals by garnering real-time insights, making smarter decisions, and enhancing customer experience. Additionally, tools like Acceldata provide comprehensive solutions to optimize data pipelines, identify latency issues, and offer end-to-end data observability across multiple platforms.