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With greater data quality comes consistency in companies' workflows

Richard Jones Archive

As companies steadily grow through these years of booming technology, they're likely taking on more staff members committed to analytics, whether they focus on collecting data from more sources or better breaking it down to uncover actionable findings. This is great news for the business world collectively, but there's a catch - the more people there are in analytics, the harder it becomes to achieve consistency in workflow.

This can become especially tricky as companies try to bring in data from multiple disparate sources. If one department is looking at information culled from people's social media posts, while another focuses on mobile apps and another looks at phone conversations with call centers, it can be difficult to bring everything together and manage it all equally effectively.

According to Waters Technology, companies need to pay more attention to this issue. Michael Shashoua, editor of Inside Reference Data, says that the information management community should do more to make data-driven work more consistent.

"Philosophers and authors may dismiss consistency as an overrated refuge for unimaginative minds," Shashoua writes. "But when it comes to industrial-strength data quality efforts, it proves to be a necessity."

The more sources of data that companies draw from, the more attention they need to pay to the little differences. Small discrepancies in addresses or email addresses could lead to big mistakes, so it may be necessary to count on data enhancement for smoothing out the wrinkles - especially in sectors such as finance, where large sums of people's money are at stake.

"It all comes down to due diligence," Shashoua stated. "Data consumers from investment firms have to be careful and deliberate about sourcing, managing and distributing data to support decision-making. Trying to speed through or cut corners on the complex mix of data management aspects just won't do."

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