We all know that every bit of an organization’s data ought to be treated equally, right?  Well, in a world where clean data is often the status quo, Julie Fawdington, Senior Director PMO at Hewlett Packard Enterprise, invites us to ask the question, “How clean is clean enough?”

Drawing on her extensive experience in data transformation, Julie’s take on data quality suggests the need for data quality differentiation. As she puts it, the stuff in her pet’s water bowl isn’t the same as what’s in her water bottle. But does this idea that not all data requires the same level of cleanliness really upend conventional wisdom? Or does it simply provide a more nuanced understanding of how to efficiently manage data in today's fast-paced business environment?

Topic: Data quality