Abstract
Background/Aims The amount of clinical data available for research is growing exponentially. As it grows, increasing the efficiency of both data storage and data access becomes critical. Relational database management systems (rDBMS) such as Oracle are ideal solutions for managing longitudinal clinical data because they support large-scale data storage and highly efficient data retrieval. In addition, they can greatly simplify the management of large data warehouses, including security management and regular data refreshes. However, the HMORN Virtual Data Warehouse (VDW) was originally designed based on SAS datasets, and this design choice has a number of implications for both the design and use of an Oracle-based VDW. From a design standpoint, VDW tables are designed as flat SAS datasets, which do not take full advantage of Oracle indexing capabilities. From a data retrieval standpoint, standard VDW SAS scripts do not take advantage of SAS pass-through SQL capabilities to enable Oracle to perform the processing required to narrow datasets to the population of interest.
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