This industrial report stems from practical experience in assessing the quality of customer databases. The process it describes unites three automated audits, -an audit of the database schema, an audit of the database structure and an audit of the database content. The audit of the database schema checks for design smells and rule violations. The audit of the database structure measures the size, complexity and quality of the database model. The audit of the database content processes the data itself to uncover invalid data values, missing records and redundant records. The purpose of these audits is to assess the quality of the database and to determine whether a data reengineering or data clean-up project is required.The existing databases of most IT users are the product of a long evolution. It began with their conception by a database designer on the basis of the information available to him at that time. This was followed by the hand coding or the automatic generation of a database schema reflecting the design. After that the database was installed and applications began to use it. As new applications came along the structure was altered or extended to accommodate them. These structural changes were often made in an ad hoc manner, so that the complexity of the structure grew and the quality sank, much like software systems according to the laws of software evolution [1]. In addition to this structural deterioration, the contents of the database became corrupted by erroneous programs storing incorrect values and deleting essential records. With large databases it is difficult to recognize such quality erosion but over time it spreads like a cancerous infection causing more and more system failures. Thus not only program quality but also data quality suffers under erosion [2].