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Getting rid of bad data quality now and in the future

Rachel Wheeler Archive

There is good data and there is bad data, reports IBM's The Big Data Hub. The former helps companies personalize marketing messages to their customers and make accurate assessments of previous sales success. The latter, on the other hand, contaminates analyses and leads decision-makers down the wrong path. Bad data quality sneaks in when firms don't have address management programs and other tools to catch errors at the point of entry. 

These mistakes include misspelled names, addresses and transposed numbers, the source adds. There are a multiple reasons for invalid data entry, from "fat fingers" while typing to incongruous database fields and deliberate fallacies. In some cases, contact data quality platforms can track incorrect entries that are part of identity theft schemes. 

Regardless of the source of the inaccuracies, businesses will find that flawed information will impact their ability to generate valuable insights. 

Another important consideration is the size of the data. The bigger the ambitions, the grander the quality controls will need to be, reports Data Quality Pro. Scalability is an important factor in analytics programs and should be considered when businesses are planning investments.