Data processing in traditional analytics was done in batches. That is, historical data processing rather than real-time data processing. This caused issues for various industries that relied on real-time data to gain insights into the current situation.

However, with technological advancements and the development of dynamic data pipelines, it is now possible to access data with minimal latency.

Institutions can track transactions, credit scores, and other financial attributes using this Data Science in Finance application without experiencing any latency.

https://youtu.be/a5KmkeQ714k