Data Warehousing and Data Mining has evolved and matured into a discipline of research and application over the last decade and a half. Wide ranging applications have emerged across various domains and Data Warehousing and Data Mining tools and applications have yielded much needed decision support to the organizations. An enormous proliferation of database in every aspect of human endeavor has created demand for designing such tools that can turn data into useful task oriented knowledge. A library is no exception in this regard. It contains data of various operations starting from the stage of procurement, stacking to subscriber transactions like issue, return, and requisition and so on. As time progresses such data accumulates to huge size and contains within it patterns which, if known, may guide the future courses of actions better with scope of effective decision making which in turn could result in money saving and better planning and utilization of resources. However, typical library management software lacks the back end support of a built in Data Warehouse which can be used for mining the volumes of data accumulated over the years of operations. Considering this to be bottom liner we have developed and implemented a Data Warehouse which can be the backend of a decision support system which rely on the discovery of patterns of transaction data in a library.