Alpha vs beta datasets
There are some ingredients that are pretty common. Just because they're commonly used, does not make them unimportant. If anything, they are the most important when it comes to food. Without common ingredients like flour or oil, it's going to be quite limiting. By the same token, very rare ingredients are not necessarily the most important. Sure, a hint of truffle (or more likely truffle oil) gives food a different and somewhat unusual flavour. However, you could probably get by, without ever having any truffle in your food. It's all about mixing ingredients, whether common or rare into that perfect mix.
Data comes in many forms. Just like food, you'll have your rare (or truffle!) datasets, many of which might be alternative data. You would expect that any alpha in these alternative datasets to be more long lasting. By contrast, with common data, which are used more commonly, we might expect that they give us more beta than alpha. After all, if it's common data, more market participants will use it, and there's a higher chance that any alpha has already been harvested.
Does this mean we should prefer to use alternative datasets instead of more commoditised and common datasets? Not really. Just because a dataset is commonly used...