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Data Quality: Poor Quality Threatens the Usability of Data Analytics

By Dick Weisinger

The National Audit Office in the UK recently found major problems in data quality that threaten a new £1 billion MoD inventory management system.

But the UK MoD is not alone with data quality problems.  A report by Teksystems found that 50 percent of IT leaders think that their organizations have data quality problems and that 60 percent think their organizations aren’t accountable for data quality issues.

The foundation of popular hot technologies like Big Data and Business Intelligence are built on the premise of high-quality accurate data.  Without high data quality, any results derived with analytics tools are highly questionable, regardless of how sophisticated the analytics techniques are.

Mary Shacklett, president of  Transworld Data, said that “dirty data is a challenge organizationally for companies.  You can ‘job out’ tasks to data cleaners, but nobody knows your own ‘dirt’ better than you do. This is because it’s hard to get data squeaky clean without knowing what it really should look like within the context of your business. It is here where data cleaning can become a painstakingly manual task.”

Kelle O’Neal, managing director of First San Francisco Partners, said that the “lack of data quality management results in inconsistent and inaccurate data, which leads to poor decisions… Poor decisions, in turn, can lead to inefficiencies, errors, additional costs or loss of business.  The inability to successfully manage data quality may also result in fines or other regulatory actions when compliance needs cannot be met within required time frames.”

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