From the course: Building Generative AI Apps to Talk to Your Data
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Using Cortex Analyst - Snowflake Tutorial
From the course: Building Generative AI Apps to Talk to Your Data
Using Cortex Analyst
- Welcome back. In the last video, you created the Semantic Model and passed it to complete, but we need better results. In this video, we will engage Cortex Analyst and see how it elegantly deals with this level of complexity. Let's think about this for a second. So imagine you are a senior manager at an international retail company that is feeling a little frustrated. You ask your Texas Equal workflow for data on sales performance by region, by store, and who the top performing sales reps are for each store and region. What you got back was the dataset that had columns of numerical IDs for the stores, regions and reps. Not very human readable. A quick filter tells you what you want to know, but now you have to spend time looking up which numerical identifier refers to which region, store and rep. The other option is to join in new columns from Dimension tables with the human readable labels for the region, store and reps. This is time consuming and pretty frustrating. What you…
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Avoiding death by dashboard4m 51s
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Setting up the app4m 58s
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Understanding the semantic model8m 18s
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Working with the semantic model4m 37s
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Using Cortex Analyst5m 56s
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From text-to-SQL to TAG: Creating table-assisted generation3m 17s
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Expanding the scope of the semantic model12m 11s
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Building the Streamlit app11m 41s
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Congratulations!3m 6s
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