The renewed momentum and practical implementation of Data Quality Management

A blog series with three different insights into Data Quality Management

Due to the changing Risk Management environment a renewed momentum in the global banking sector has been created. This might cause increased Data Quality Management challenges. In this blog series the complexity of these challenges will be reduced by means of a six-step process. This process introduces the steps towards a strong Data Quality Management foundation and it will discuss in-depth how to translate the data requirements into practice.

Blog 1: Data Quality Management: renewed focus and momentum in Banking sector

This blog is our introductory blog on Data Quality Management in finance and risk departments in banking. It introduces the internal and external drivers behind the renewed momentum in this sector.

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Blog 2: The foundation for a strong Data Quality Management Practice

Due to the increased quantity and complexity of regulatory risk metrics Data Quality Management might seem difficult to manage. This blog aims to unfold this complexity by using a six-step Data Quality Management process. In this blog the first two steps will be discussed.

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Blog 3: The guide to set up Data Quality monitoring in practice

In this third and final blog the last four steps of the Data Quality Management process are presented. The blog outlines how to translate data requirements into data quality rules and monitoring process including the Deloitte accelerator tool and our best practices.

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