Dremio, an open data lakehouse vendor, is embracing generative AI with two new capabilities for its platform. The text-to-SQL feature allows users to receive insights from their data by using natural language inputs, while autonomous semantic layer uses generative AI to catalogue users’ data and create descriptions for easy exploration. These processes aim to make using data a simpler process. Additionally, Dremio is offering vector database capabilities to enable users to build AI-powered applications, without data silos. The vector database will allow users to store and search embeddings for data elements that will retrieve similar or related reviews based on meaning. Dremio is excited to provide these powerful generative AI tools to ease data exploring, engineering, science, and analytics.
Frequently Asked Questions (FAQs) Related to the Above News
What is Dremio?
Dremio is an open data lakehouse vendor, providing a platform for data exploration, engineering, science, and analytics.
What new capabilities is Dremio introducing?
Dremio is introducing two new capabilities - text-to-SQL feature and autonomous semantic layer - that use generative AI to make exploring and using data simpler. Dremio is also offering vector database capabilities for building AI-powered applications without data silos.
What is the text-to-SQL feature?
The text-to-SQL feature allows users to receive insights from their data by using natural language inputs. This feature uses generative AI to convert text inputs into SQL queries, making data exploration simpler.
What is the autonomous semantic layer?
The autonomous semantic layer uses generative AI to catalogue users' data and create descriptions for easy exploration. This layer creates a unified view of the data and automates the process of metadata management.
What are vector databases?
Vector databases are databases that allow users to store and search embeddings for data elements. This allows for the retrieval of similar or related reviews based on meaning, making it useful for building AI-powered applications.
What is the goal of these new capabilities?
The goal of these new capabilities is to make exploring, engineering, science, and analytics of data simpler and more accessible for users.
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