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With your input, we released more than 200 new capabilities across the Tableau platform in 2020. In every release, we're making Tableau easier to use, more powerful, and simpler to deploy to support governed data and analytics at scale. In 2020, we added the ability to write to external databases so you can use cleandata anywhere.
It can be gradually “enriched” so the typical hierarchy of data is thus: Raw data ↓ Cleaneddata ↓ Analysis-ready data ↓ Decision-ready data ↓ Decisions. For example, vector maps of roads of an area coming from different sources is the raw data. Licensing FAIR data for reuse. Ferreira, K.
With your input, we released more than 200 new capabilities across the Tableau platform in 2020. In every release, we're making Tableau easier to use, more powerful, and simpler to deploy to support governed data and analytics at scale. In 2020, we added the ability to write to external databases so you can use cleandata anywhere.
Ryan Cairnes Senior Manager, Product Management, Tableau Hannah Kuffner July 28, 2020 - 10:43pm March 20, 2023 Tableau Prep is a citizen data preparation tool that brings analytics to anyone, anywhere. With Prep, users can easily and quickly combine, shape, and cleandata for analysis with just a few clicks.
Ryan Cairnes Senior Manager, Product Management, Tableau Hannah Kuffner July 28, 2020 - 10:43pm March 20, 2023 Tableau Prep is a citizen data preparation tool that brings analytics to anyone, anywhere. With Prep, users can easily and quickly combine, shape, and cleandata for analysis with just a few clicks.
I don’t think we would have been able to write a paper about just “vector-database-plus-language-model.” We have papers from 2020 where we showed that these models hallucinate less than regular parametric models. But what folks generally underestimate, or just misunderstand, is that it’s not just generically good data.
I don’t think we would have been able to write a paper about just “vector-database-plus-language-model.” We have papers from 2020 where we showed that these models hallucinate less than regular parametric models. But what folks generally underestimate, or just misunderstand, is that it’s not just generically good data.
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