Analyses & optimisation of data quality

Challenges

For lacking data quality often old and/or grown systems are causal. Also lacking operational possibilities of the data administration can be causal.

Some examples of data quality problems:

Limited field length

Caused by limited field length some Information was abbreviated in the past: “Steven v.Wendehals ,Mister Brown trav. sales. o. Hofman Inc c/o trading Inc.”

Wrong field content

In the road fields of the address delivery information is found: “Christine a. John Greenfield High str. 33/2 Flat. 222 Staircase. 2”.
In old or grown systems the name field(s) have been misused for other information, which is not intended to be there. This could be contact names, department names, deviating invoice recipients, nominated representatives or delivery information.

Duplicates

For one and the same customer contracts have been setup in several ways using different wordings: “United Kingdom Insurances Inc” and “U.K. Insurances” or “U. Kingd. Insurances Incorporation”. The clerk has to do a good guess to find out which contract is the right one.

Complex structures, no fitting fields

Complex structures, like at public administrations or the different owner communities, had to be illustrated in few fields as completely as possible. The result for an address field for example has been something like this this: “City of XY Dept. 7 Facility Services (Building H7) Room UA210.”

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