This article begins by presenting and discussing the distinction between record-oriented and pattern-oriented search. Examples of record-oriented (or item-oriented) questions include: “What (or how many, etc.) glass items made prior to 100 A.D. do we have in our collection?” and “How many paintings featuring dogs do we have that were painted during the 19th century, and who painted them?” Standard database systems are well suited to answering such questions, based on the data in, for example, a collections management system. Examples of pattern-oriented questions include: “How does the (apparent) production of glass objects vary over time between 400 B.C. and 100 A.D.?” and “What other animals are present in paintings with dogs (painted during the 19th century and in our collection)?” Standard database systems are not well suited to answering these sorts of questions (and pattern-oriented questions in general), even though the basic data is properly stored in them. To answer pattern-oriented questions it is the accepted solution to transform the underlying (relational) data to what is called the data cube or cross tabulation form (there are other forms as well). We discuss how this can be done for non-numeric data, such as are found widely in museum collections and archives. Further we discuss and demonstrate two distinct, but related, approaches to exploring for patterns in such cross tabulated museum data. The two approaches have been implemented as the prototype systems Homer and MOTC. We conclude by discussing initial experimental evidence indicating that these approaches are indeed effective in helping people find answers to their pattern-oriented questions of museum and archive collections.