When transactions are not serializable (which is often the case in multi-user environments).
Lost Updates: This event occurs when two transactions read the same data and both attempt to update that data, resulting in the loss of one of the updates. For example: Transaction 1 and Transaction 2 read the same row of data and calculate new values for that row based upon the original values read. If Transaction 1 updates the row with its new value and Transaction 2 then updates the same row, the update operation performed by Transaction 1 is lost.
Dirty Reads: This event occurs when a transaction reads data that has not yet been committed. For example: Transaction 1 changes a row of data, and Transaction 2 reads the changed row before Transaction 1 commits the change. If Transaction 1 rolls back the change, Transaction 2 will have read data that never really existed.
Nonrepeatable Reads: This event occurs when a transaction reads the same row of data twice and gets different results each time. For example: Transaction 1 reads a row of data, then Transaction 2 modifies or deletes that row and commits the change. When Transaction 1 attempts to reread the row, it will retrieve different data values (if the row was updated) or discover that the row no longer exists (if the row was deleted).
Phantoms: This event occurs when a row of data matches some search criteria but isn’t seen initially. For example: Transaction 1 retrieves a set of rows that satisfy some search criteria, then Transaction 2 inserts a new row that contains matching search criteria for Transaction 1’s query. If Transaction 1 re-executes the query that produced the original set of rows, a different set of rows will be returned (the new row added by Transaction 2 will now be included in the set of rows produced).