Keeping It Clean
The Importance of Well-Engineered Data
As companies turn to Big Data analysis to transform their business models, ensuring the quality of that data has become more important than ever.
Companies that don’t make well-engineered data a priority end up hurting their bottom line. IBM estimates that poor quality data costs the U.S. economy about $3.1 trillion per year.
Even the most thorough data is useless if it’s mislabeled or formatted incorrectly. Instead of spending time and money to clean up data after the fact, it’s much better for the data to be well-engineered in the first place. By implementing best practices, companies can ensure their collected data is useful, reliable, and easy to process.
Doing It Right
Daniel Newman, writing in Forbes, emphasizes that it takes far less work to collect and format data correctly than it does to clean it up:
Establish clear guidelines on where and how data is collected to prevent “data wildness,” and make sure those standards are consistently honored. Take time to vet sources as “trustworthy,” and take preemptive steps to ensure it stays that way. A little work on the front end will prove hugely valuable when it comes to putting your data to use.
The source of data can also have a direct impact on its quality. If your business purchases third-party data from an outside source, it has no direct control over its quality. Although it requires an ongoing investment of time and money, directly collecting and managing data will let your companies ensure its usability.
We Can Help
If your business is having trouble collecting and managing the information you need to thrive in today’s data-intensive world, the data science experts at LMS can help. Call us at 800.257.5902 to learn more or reach out to us today at [email protected]