The quality of data contained in the enterprise information systems has significant impact, both from the internal business decision-making perspective and the external regulatory and shareholder obligations. This paper addresses data quality assessment in business processes by proposing a modeling framework to quantify the data quality in an information processing system. We present a business process modeling framework for data quality analysis and develop the mathematical formulation for error propagation. This is overlaid with a business controls framework where the placement and effectiveness of the controls alter the propagation of errors. This framework enables the estimation and management of data quality when faced with changes in various aspects of the business process. It also allows the formulation of optimization problems that trade off the cost of business controls with the level or cost of the resultant data quality. We illustrate the modeling framework and analyses with a revenue management process.