In the late 1990s, we were hired by a client to lead a data quality initiative on a large project that involved migrating data from legacy systems to open architecture. In developing the program for our client, we immersed ourselves in a tremendous amount of literature from respected authors on principles of data quality. What we discovered is that a great deal of the data quality work we reviewed was focused on principles and theory but lacking in the area of implementation.

As a result, we struggled with exactly how to design and implement a practical data quality program for our client. What our client required was a straightforward methodology for implementing, practicing and promoting data quality. Our task was to develop a methodology that was repeatable with well-defined objectives and deliverables. The result was the data quality cycle 1.0.

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