The role of data quality in AI and ML — a full guide.
Artificial Intelligence (AI) and Machine Learning (ML) are becoming a prominent part of the business landscape as we continue to advance through the digital age. But is it as simple as plugging your data into some code? Are businesses missing out on the true potential of these powerful approaches to data science due to poor data quality?
In this guide, we aim to dissect the importance of high-quality data and the harm that can come from poor quality data, as they are used in AI and ML.
The guide covers
● An overview of the current data landscape
● The relationship between AI and data quality
● How bad data harms AI and ML
● How to achieve high data quality
● Data quality and ROI
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