Shuffling techniques are methods used to rearrange the order of items, commonly applied in card games and data management. The most popular technique is the riffle shuffle, where a deck of cards is split into two halves and interleaved. Other methods include the overhand shuffle and the pile shuffle, each offering different levels of randomness. In data management, shuffling techniques help ensure that data is randomly distributed, which is crucial for tasks like machine learning and statistical sampling. These techniques improve the reliability of results by minimizing bias and ensuring that samples represent the entire dataset effectively.