How would you explain the differences between stream processing and data processing to someone from the business department?

When explaining the differences between stream processing and data processing to someone from the business person who may not have a technical background, it's important to use non-technical language and relatable examples. Here's a simplified explanation:

Stream Processing:

Think of stream processing as being similar to monitoring a live news feed. In finance, stream processing is like keeping a constant eye on real-time data as it flows in, just like you watch news updates as they happen.

Imagine you're tracking stock prices, and you want to know immediately when a stock price changes. Stream processing allows you to stay updated in real-time, so you can react quickly to any price fluctuations. It's like having a live dashboard that shows you the latest stock prices as they change.

Data Processing:

On the other hand, data processing is like looking at a report or statement that summarizes a whole day's worth of news. In finance, data processing involves taking a batch of data that has accumulated over a period, like a day or a week, and then analyzing it all at once.

For example, you might want to calculate the total sales for a week or generate a monthly financial report. This process involves taking all the data that has been collected and processing it together as a batch. It's like reading a newspaper at the end of the day to get a summary of what happened.

In summary, stream processing is about real-time monitoring and immediate reactions, while data processing is more about looking at a larger set of data over a specific period to gain insights or create reports. Both are important in finance, as they help in making informed decisions and managing financial data effectively.