Artificial intelligence and machine learning can generate quality predictions and analysis, but first require organizations be trained on high quality data, starting with the six dimensions of data quality.
The old adage of computer programming — garbage in, garbage out — is just as applicable to today’s AI systems as it was to traditional software. Data quality means different things in different contexts, but, in general, good quality data is reliable, accurate and trustworthy.
“Data quality also refers to the business’ ability to use data for operational or management decision-making,” said Musaddiq Rehman, principal in the digital, data and analytics practice at Ernst & Young.
