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Companies find analytics insights depend on data quality

Paul Newman Archive is a new social network that uses customer-provided information and analytics to identify which participants might make good "friends", gaming opponents or connections for others on the site. However, its success as a client-matching service is contingent on data quality, reports Search Data Analytics.

If the company doesn't verify the vast amount of data coming through its networking sites (around 50 billion log entries per month), the site's overarching goal could be compromised, the source adds. To prevent data quality issues, Tagged has developed a robust strategy and addresses its content on a regular basis.

"Sweat the small stuff to catch the big problems," Tagged co-founder and chief technology officer Johann Schleier-Smith told the news source. "Even little discrepancies, such as numbers that should add up but are off by just a little, are often indicators of serious issues."

This same idea should be applied to other companies that plan to use analytics to improve  processes within their operations, such as small businesses that are using their CRM systems for forecasting and marketing analytics, according to eWeek. Without tools to verify data across departments, they may find it difficult to analyze information inputted by different individuals.