The building blocks of data organization are datasets. Each dataset can pull and unify data from multiple data sources. Each dataset resides in a destination.
In simple terms, Qluster's connector reaches out to your data source, receives data from it, and writes it to your dataset at your destination.
A data source answers the following basic questions:
There can be multiple data sources for each data set. However, typically each data source corresponds to a specific type of data from a particular data vendor.
For example, a marketplace company can have an "inventory" dataset. This dataset lives in a specific database instance. In Qluster terms, the database instance is called a destination.
The marketplace company is pulling inventory data from multiple stores. Each store has its way of providing inventory data to the marketplace company.
For Example:
In this case, the inventory dataset has three data sources, one for each vendor. Each data source can have its own "rules".
For example, vendor 1 calls a column "brand". Vendor 2 calls the same column "manufacturer". Once the data is in the dataset, we want to have a "brand" column showing data from both vendors.