Total Data Quality Management and Total Information Quality Management Applied to Costumer Relationship Management

Data quality (DQ) is an important issue for modern organizations, mainly for decision-making based on information, using solutions such as CRM, Business Analytics, and Big Data. In order to obtain quality data, it is necessary to implement methods, processes, and specific techniques that handle information as a product, with well established, controlled, and managed production processes. The literature provides several types of quality data management methodologies that treat structured data, and few treating semi- and non-structured data. Choosing the methodology to be adopted is one the major issues faced by organizations, when challenged to treat the data quality in a systematic manner. This paper makes a comparative analysis between TDQM -- Total Data Quality Management and TIQM -- Total Information Quality Management approaches, focusing on data quality problems in the context of a CRM -- Costumer Relationship Management application. Such analysis identifies the strengths and weaknesses of each methodology and suggests the most suitable for the CRM scenario.

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