What is the concept of partitioning in Pig?

In Pig, partitioning refers to dividing data into different parts based on specified keys in order to more efficiently manipulate and analyze the data. By partitioning the data, it can be grouped into different sections, allowing for quicker querying, filtering, and analyzing of the data. Data can be partitioned based on the values of a single column or a combination of values from multiple columns. In Pig, partitioning can help users handle large datasets more effectively.