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Why Clean Data Is Non-Negotiable in the AI Era with Lizz Hellinga

Salesforce Admins Podcast

Release Date: 12/07/2023

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Today on the Salesforce Admins Podcast, we talk to Lizz Hellinga, Consultant and Salesforce MVP.

Join us as we chat about why clean data is more important than ever if you want to leverage the potential of generative AI.

You should subscribe for the full episode, but here are a few takeaways from our conversation with Lizz Hellinga.

Generative AI needs clean data

I brought Lizz on the pod to bring you an important message: clean data is no longer optional. “If your data isn’t ready for generative AI, your business isn’t ready,” she says. This was the theme of her presentation at Florida Dreamin’, and I thought it was something every admin needed to hear.

Everyone is excited about the new generative AI tools coming to Salesforce and it’s potential to revolutionize how we use data. Something that Lizz feels gets lost in the conversation, however, is that these insights will only be as good as the data you use to generate them. That’s why clean data is more important than ever before.

What is bad data?

This naturally begs the question, what makes for bad data? Some common examples Lizz shares include:

  • Duplicate data

  • Inaccurate data

  • Incomplete data

  • Stale data

  • Hoarded data

Hoarded data sticks out to me as something that isn’t discussed as much. As Lizz explains, not too long ago we went through a phase of “more data = good.” This has led many organizations to blindly hold onto data they’ll never use but are too afraid to throw away.

For Lizz, the key here is to work with your stakeholders to create a data governance policy. That way you’re clear on what data quality means for your organization and what data you don’t need to retain. As Lizz points out, reporting is a good opportunity to highlight why this is important to everyone involved.

How to get started cleaning your data for generative AI

When you’re looking at what data is most important to clean up for generative AI, Lizz recommends that you start by documenting the process you’re going to be working with. What are the essential data points in that journey? How does the data come in, and how can you make that easier?

It’s hard to get people motivated to clean up their data. Whether it’s the end of the quarter or the beginning of the new one, it’s never the right time. For Lizz, you need to talk about the why. You need to sell your stakeholders on what generative AI can do to make their lives easier, and why you need high-quality data to do that.

We get into a lot of specifics with Lizz on the podcast, so be sure to take a listen to learn more. And remember, now’s the time to clean up your data!

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