Machine learning modules are only as good as the data they ingest
“If data is not clean, if it’s not accessible, if it isn’t stitched together to form a strong foundation, the machine learning and artificial intelligence capabilities built on top of it will have problems,” warns Ashok Srivastava, senior vice president and chief data officer at financial software provider Intuit.
Machine learning success is highly dependent on having relevant and high-quality data. If the machine learning models are informed by bad data, the results they generate may be misleading—or even incorrect.
Download What Leaders Must Know About Data to Drive Success With Machine Learning for insight that will help you create a data management strategy that will continuously improve the quality, integrity, access, and security of data. In this guide, we share:
- What is needed to leverage data for machine learning
- How to develop a data management strategy in support of machine learning
- Why a modern, efficient data model is need for machine learning success
