Challenges and Opportunities in Information Quality

Summary form only given. Each year companies are spending hundreds of thousands of dollars in data cleansing and other activities to improve the quality of information they use to conduct business. The hidden cost of bad data - lost opportunities, low productivity, waste, and myriads of other consequences - is believed to be much higher than these direct costs. One study estimates this combined cost due to bad data to be over U$30 billion in year 2006 alone. As business operations rely more and more on computerized systems, this cost is bound to increase at an alarming rate. Information quality (or data quality) has been an integral part of various enterprise systems such as master data management, customer data integration, and ETL (extraction, transform, and load). We are witnessing trends of renewed awareness and efforts, both in research and practice, to address information quality collectively as an independent value in enterprise computing. International organizations such as EPC Global and the International Standardization Organization (ISO) have launched working groups to study and possibly introduce standards that can be used to define, assess, and enhance information quality throughout the supply chain. Issues in information quality range over multiple disciplines including software engineering, databases, statistics, organizational operations, and accounting. The scope and goal of information quality management would depend on the organization´s objectives and business models. Assessing the impact of data quality is a complex task involving key business performance indexes such as sales, profitability, and customer satisfaction. Methods of assuring data quality must address operational processes as well as supporting technologies. This panel, with input from experts from both academia and industry, explores the challenges and opportunities in information quality in the dynamic environment of today´s enterprise computing.