Scrutinizing Data Quality Needs

Last week in this space, I considered whether data quality depends on standards compatibility or firms' relationships with data providers. From comments this sparked in Inside Reference Data's LinkedIn discussion group, it's also evident that data quality needs can depend on what function the data has to serve within the enterprise.

Firms are well advised to get data from multiple sources, says industry data management veteran Tim Vogel. "The more sources a firm can purchase yields data that can be cross-vetted," he says. Using multiple sources doesn't make multiple standards a real concern, as there are ways to correct discrepancies, Vogel adds.

"If there is an incorrect record, you can reach out to the help desk," he says. "If you want a new field or multiple fields added to a product, that will take time to achieve. You have to support this need internally." By the time adjustments can be made, however, firms tend to figure out the data issues themselves, according to Vogel.

All in all, however, large firms or firms trading algorithmically have high data quality requirements. Therefore, the more vendors they use, the better their chances of catching incorrect data, particularly corporate actions data, explains Vogel.

Even so, the cost of utilizing multiple providers is still a consideration, which brings the discussion back to the fact that costs can vary from vendor to vendor, and those different types of users within a firm, as previously mentioned, can each have different budget levels. So perhaps cost, for better or for worse, is a secondary consideration to the effectiveness of getting the data quality and how a firm can increase that.

As always, these Editor's Views also are posted to the LinkedIn group, and are always open to reply and comment. If you see this issue or any issue differently, Inside Reference Data takes note.