The Salesforce Admins Podcast
Agentforce’s Best Friend: Clean, Reliable Data
Jan 16, 2025
Join Lizz Hellinga, a Consultant and Salesforce MVP specializing in data quality, as she emphasizes that clean data is crucial for harnessing the power of generative AI. Lizz warns that poor-quality data can undermine AI insights. She shares that bad data can include duplicates, inaccuracies, and outdated records, highlighting the need for strong data governance. Practical steps for data cleanup and engaging stakeholders in the process are also discussed, making a strong case for the importance of maintaining data integrity in today’s tech landscape.
29:25
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Quick takeaways
- Clean data is critical for effective AI deployment since the quality of data directly impacts the reliability of AI insights and outputs.
- Implementing robust data governance policies and engaging stakeholders are essential steps for organizations to manage bad data and improve overall data quality.
Deep dives
The Importance of Clean Data for AI
Clean data is essential for organizations looking to leverage artificial intelligence effectively. Without clean data, companies may find that their AI implementations yield inaccurate or unhelpful results, ultimately hindering their business objectives. The importance of maintaining data quality is underscored by the realization that generative AI applications rely heavily on pristine data to produce meaningful outputs. Moreover, incorporating frameworks such as data governance policies becomes increasingly vital to ensure that clean data practices are systematically integrated into organizational processes.
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