Imagine that you have a lot of candies, and you need to count them. Now, you can count them one by one, which could take a really long time, or you can group them into groups of 10, 100, or even 1,000 candies.
In data, you can think of orders of magnitude as similar groupings. Instead of candies, we are talking about numbers. When we talk about orders of magnitude, we're really talking about how big or small a number is compared to other numbers.
For example, 1 is one order of magnitude smaller than 10 because it's 10 times smaller. Similarly, 10 is one order of magnitude smaller than 100 because it's 10 times smaller. 100 is one order of magnitude smaller than 1,000 because it's 10 times smaller.
Now, when we talk about really big or really small numbers, it can be hard to keep track of all those zeros. It's much easier to group them into orders of magnitude. For example, a billion is three orders of magnitude larger than a million.
In data, orders of magnitude are often used to talk about data storage or processing power. For example, a typical computer can process around 10 million instructions per second (10^7), while a supercomputer might be able to process 10 billion instructions per second (10^10).
So, orders of magnitude are just a way of grouping really big or really small numbers together to make them easier to understand and work with.