Data quality framework for small companies

Today computers are an integral part of businesses. The data they produce are used to make business decisions every day. The decisions made are only as good as the data. It is important for organizations to examine the quality of their data. Data quality problems must be addressed and processes must be put in place to prevent future occurrences. However, data quality is often not a priority in organizations. Data quality must compete with other corporate priorities for limited corporate funds. This is even more pronounced during a recession. It is essential especially for small businesses to have a low cost method to address data quality. The goal of this research was to use process improvement to extend an existing theoretical model in the field of Data Quality to a new field of practice that could be used by small businesses. The existing theoretical model is called Total Data Quality Management (TDQM). This research modified TDQM to create a framework which was less resource intensive and more cost effective. The goal of this research was to make data quality attainable for small companies.