Data quality may not be the most exciting aspect of big data plans, but it's vital to their success.
By Rachel Wheeler
Nov 9 2012, 22:55 PM
Data quality may not be the most exciting aspect of big data plans, but it's vital to their success. Companies that don't prioritize data quality efforts by assigning responsibility to highly qualified individuals and regularly monitoring efforts could not only find that they have wasted their investments, but the issues that arise could have permanent consequences.
In a recent incident, insurance provide[r] Prudential was fined by the British Information Commissioner's Office for a breach of the Data Protection Act stemming from data quality issues. The act states that "personal data shall be accurate and, where necessary, up to date". However, the company accidentally merged the information stored in two clients' records who shared a birthday and name.
Companies like Prudential that have approximately 6 million customers should implement better data quality tools to prevent this from taking place, since there was a strong likelihood its clients shared a common name and other basic identifying information, Information Age adds.
If enterprises take a more proactive approach by developing better relationships between company heads such as chief financial officers (CFOs) and chief risk officers (CROs), they can join forces on data quality issues to prevent potentially damaging oversights.
All professionals must take responsibility for data quality rules
- Nov 25 2014, 12:31 PM
Data quality should be a key goal in business.
Using accurate data to understand customer behavior
- Nov 11 2014, 12:34 PM
One great use for data quality is in understanding customer behavior.
Examining the pros and cons of retargeting customers in marketing
- Nov 10 2014, 13:09 PM
Part of the beauty of data quality is you can rely on it again and again.