Sponsored by: Anomalo | Data Quality: The Greatest Challenge for Enterprise GenAI Adoption
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Science and Machine Learning |
INDUSTRY | Enterprise Technology, Media and Entertainment, Financial Services |
TECHNOLOGIES | AI/Machine Learning, GenAI/LLMs, Governance |
SKILL LEVEL | Intermediate |
DURATION | 40 min |
DOWNLOAD SESSION SLIDES |
Data quality is emerging as the greatest challenge for GenAI adoption in the enterprise. GenAI pushes all industries to consider their GenAI readiness, data quality initiatives, and ability to scale. Enterprise internal data must be brought to the model as there is no “off the shelf” model that will “just work” for enterprise use cases. High quality data is integral to enterprise GenAI success as low quality data will propagate. Anomalo’s data quality platform helps innovative teams bring trusted high quality data to GenAI models that are personalized to enterprise use cases. In this session, discover how Anomalo’s innovative enterprise customers within the Databricks ecosystem, leverage, deploy, and scale their data quality initiatives.
SESSION SPEAKERS
Amy Reams
/Vice President, Business Development
Anomalo
Taly Kanfi
/Director, Data Solutions Architects
Anomalo