Remove Accessibility Remove Structured Data Remove Unstructured Data
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Now in Public Preview: Processing Files and Unstructured Data with Snowpark for Python

Snowflake

With this new Snowpark capability, data engineers and data scientists can process any type of file directly in Snowflake, regardless if files are stored in Snowflake-managed storage or externally. Previously, working with these large and complex files would require a unique set of tools, creating data silos. ” U.S.

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Fueling Enterprise Generative AI with Data: The Cornerstone of Differentiation

Cloudera

By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.

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Accelerate AI Development with Snowflake

Snowflake

However, scaling LLM data processing to millions of records can pose data transfer and orchestration challenges, easily addressed by the user-friendly SQL functions in Snowflake Cortex. Traditionally, SQL has been limited to structured data neatly organized in tables.

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Empower Your Cyber Defenders with Real-Time Analytics Author: Carolyn Duby, Field CTO

Cloudera

Unstructured data not ready for analysis: Even when defenders finally collect log data, it’s rarely in a format that’s ready for analysis. Cyber logs are often unstructured or semi-structured, making it difficult to derive insights from them.

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A Major Step Forward For Generative AI and Vector Database Observability

Monte Carlo

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories.

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Data Warehouse vs Big Data

Knowledge Hut

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.