Data are values that are either quantitative or qualitative. They are merely values or descriptive text without structure and context, and subject to interpretation. Data are raw, and unorganized, and often times, may appear as a merely random collection of text and values. For instance, a data can be a set of scores from a test of students written in no particular order. Without knowledge that those are actually scores, they might appear as random numbers to an outsider.
Information, on the other hand, can be interpreted properly. Information is what you would get after processing, and organizing your data. Information also has to be interpreted in a given context, and is not random at all. For instance, the test scores could be presented in a tabular form along with the class ID of each student and then the average and standard deviation can be calculated. The average represents the mean score, while the SD the spread of the student's score. This gives us, from the raw data (scores) the information about the performance of the class.
In another sense, we can say that the data is what is given (or probably what was recorded from the event), and information is what we get from the data, after it has been analyzed, processed, organized, and interpreted.