Strong consistency is a property of data systems that ensures any read operation returns the most recent write. This means that once a change is made to the data, all subsequent reads will reflect that change immediately. It guarantees that all users see the same data at the same time, which is crucial for applications requiring accurate and up-to-date information. In distributed systems, achieving strong consistency can be challenging due to network delays and failures. Techniques like consensus algorithms, such as Paxos or Raft, are often used to maintain strong consistency across multiple nodes. This ensures that even in a distributed environment, data remains reliable and synchronized.