In my column last month, I described the data transformation chain. In summary, all systems that transform raw data about business entities into information that can be used for business insight must go through a set of common steps:
The quality derived at each step in the transformation is heavily dependent on the quality of the preceding steps. Thus, solving data quality problems, particularly those found when consolidating across databases, requires that you start remediation at the top and work down the chain. The example that I will use to illustrate the logic is a problem I have encountered at three different companies. In all three cases, the CEO asked what appeared to be a simple question: What 10, 25 or 50 companies are our largest customers? The last time I checked, smart and hardworking people at all three companies were still trying to answer the question. In all three companies, significant software expenditures were made for state-of-the-art customer data integration (CDI) and/or master data management (MDM) software, but the answer continues to elude the teams working on the question.
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