The proliferation of Windows-based programs for PCs, together with the requirement of many business managers for faster responses to their information needs, has led many business end-users to create, maintain, and query their own databases. These individuals use the output of these queries as the basis for operational, tactical, and strategic decisions. To maximize the benefit of end-users' time, querying these databases must be as efficient as possible. Of even greater importance, the effectiveness of managers' decision-making is directly related to the quality of the information extracted. Because end-user querying is error prone, characterizing the sources of query errors and using that knowledge to improve the effectiveness of end-user query development can improve the quality of information available for decision-making. IS professionals typically design databases in third normal form. End-user databases designed with the help of IS professionals are also likely to be in third normal form. Although third normal form is better for data capture, prior research indicates third normal form is not necessarily the most appropriate normal form for querying. This paper reports the results of an in-depth experiment into the effects of normalization level on the efficiency and effectiveness of end-user querying. The results confirm earlier findings that end-users querying first normal form data structures were both more efficient and more effective than those querying third normal form data structures. This research extends prior research by examining the specific areas where first normal end-users outperform third normal form end-users. In particular, the experiment revealed that first normal form end-users made significantly fewer errors in relation to attribute selection, table selection, and row restriction.