What Is Machine Learning?
Why is Data Quality Important to Machine Learning?
Data-intensive projects consistently have a single point of failure: data quality.
As a result, assessing and improving data quality should be the first step of any machine learning project. This includes checking for consistency, accuracy, compatibility, completeness, timeliness, and duplicate or corrupted records. Often, manually cleansing data is an impossibility, may take months or be cost-prohibitive.
For any company that wants to participate in the machine learning revolution – one that is already disrupting today’s business landscape – data quality is an issue that simply cannot be avoided.
Does your business need assistance in data management and improving data quality for machine learning?
Or do you need help creating data solutions in order to leverage other businesses?
Robinson Ryan is driven by the belief that the best data promotes the best business, and we are here to support you. Contact us today
