When a company decides to undertake a data governance initiative, the project leaders may look for guidance and direction by studying what other organisations have done to reel in contact data quality or other records.

But that quest for a sure-fire model could be fruitless, and as one expert argues, every data situation is different.

Jill Dyche said in an interview with Data Quality Pro that one of the challenges to building a data governance template is that every group's needs vary, and there is no one-size-fits all strategy.

"Unlike other strategic initiatives that involve IT, data governance needs to be designed," Dyche noted. "The cultural factors, the workflow factors, the organisational structure, the ownership, the political factors, all need to be accounted for when you are designing a data governance roadmap."

The problem with searching for a common template, she continues, is that some people assume they can just adopt it and forget about it.

Rather than picking a blueprint and sticking to it, data quality and governance projects require company leaders to constantly reassess the direction the cleansing process is taking and adapt their policies to fit what's stored on their databases.