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The Rise of Unstructured Data

Cloudera

Here we mostly focus on structured vs unstructured data. In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else.

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5 Reasons Manufacturers Should Move ERP Data to Snowflake to Supercharge Analytics

Snowflake

Advanced analytics help manufacturers extract insights from their data and improve operations and decision-making. But for manufacturers, it’s often challenging to perform analytics with ERP data. A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible.

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Streamline Operations and Empower Business Teams to Unlock Unstructured Data with Document AI 

Snowflake

From unstructured data to boundless opportunities The potential applications for this technology are vast — from small financial firms to manufacturing conglomerates, from invoice reconciliation to evidence discovery. Take, for example, Northern Trust, the 134-year-old financial services company headquartered in Chicago.

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The Dawn of the AI-Native Data Stack - Part 1

Data Engineering Weekly

This next phase, the AI-Native Data Stack , will fundamentally alter how we build, maintain, and scale data systems. To understand this evolution, let's draw parallels from a seemingly unrelated field—manufacturing—and its historical transformation. What do they have in common? Tools like cursor.ai

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Manufacturing Data Ingestion into Snowflake

Snowflake

Accessing data from the manufacturing shop floor is one of the key topics of interest with the majority of cloud platform vendors due to the pace of Industry 4.0 also known as the Fourth Industrial Revolution, refers to the emerging trend of technological transformation in manufacturing and related industries. Industry 4.0,

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GenAI-Driven Quality Control: Achieving Zero Defects in Manufacturing

RandomTrees

Today’s manufacturing landscape is truly on a whole new level, and getting perfection has never been more intense. This is where Generative Artificial Intelligence, simply known as GenAI, comes in and is currently being used to transform quality assurance in manufacturing processes.

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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.