Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
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The Future of Data Catalogs --Shinji Kim, Snowflake/SelectStar
Shinji Kim, founder of SelectStar (acquired by Snowflake), joins me to talk about the deal, and why in a few years we may stop calling these things "data catalogs" at all as the category evolves into a living AI context layer.
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
Context-Aware SQL and Metadata with Shinji Kim
A common challenge in data-rich organizations is that critical context about the data is often hard to capture and even harder to keep up to date. As more people across the organization use data and data models get more complex, simply finding the right dataset can be slow and create bottlenecks.
…
موتور جستجوی پادکست
می توانید از وب سایت ما برای جستجوی پادکست های3,828,650و قسمت های196,474,281بر اساس افراد، مکان ها یا موضوعات استفاده کنید.
سرمایه‌گذاری روی دانش بیشترین بازده را دارد؛ پس پادکست گوش می‌دهم.
‐ Benjamin "Llamacorn" Franklin
ویرایش
از کمک شما برای بروز نگهداشتن پایگاهدادههای پادکست سپاسگزاریم
