Balancing data quality with data simplicity

Every company that prioritizes collecting information about its customers and B2B clients has an interest in maintaining data quality. Analytics-driven initiatives are a growing trend in business, but they're all for nothing if organizations aren't able to ensure the accuracy of their data. If data scientists are working with outdated addresses, incorrect financial information or any other kind of data that's riddled with errors, they're likely to waste time and money on mistaken business plans.

There are other values that companies must keep in mind when they venture into analytics, though. Waters Technology points out that what's just as important as data quality is data simplicity. In other words, if companies have extremely complex processes for gathering data and turning it into meaningful business results, it's probably best for them to focus on eliminating extraneous steps.

For example, by narrowing down the spectrum of sources they use for collecting data, companies can prevent problems with duplicate entries in their databases. By collecting only the most relevant information and avoiding the topics that aren't important, they can reduce clutter and bring renewed focus to their undertaking. For many reasons, simplicity is key.

Michael Shashoua, editor of Inside Reference Data, believes that in all of their analytical programs, companies can benefit from simplifying their approach.

"The common thread in all these initiatives and requirements is that on the face of it, their aims are to make it simpler to generate and identify accurate data and, by extension, make it easier to manage," Shashoua stated, according to Waters. "Whether the data is identifiers, more general securities and counterparty data or entire portfolios, the complexities involved in following these initiatives vary in the level of challenge they present to data professionals."

Data-driven programs are a tremendous drain on companies' time and money. It's beneficial for CIOs to narrow their focus to only their simplest, most relevant goals before getting started.