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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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The Emerging Role of AI Data Engineers - The New Strategic Role for AI-Driven Success

Data Engineering Weekly

The Critical Role of AI Data Engineers in a Data-Driven World How does a chatbot seamlessly interpret your questions? The answer lies in unstructured data processing—a field that powers modern artificial intelligence (AI) systems. How does a self-driving car understand a chaotic street scene?

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Generative AI and Its Role in Innovation for Telecom Services

RandomTrees

Understanding Generative AI Generative AI describes an integrated group of algorithms that are capable of generating content such as: text, images or even programming code, by providing such orders directly. The considerable amount of unstructured data required Random Trees to create AI models that ensure privacy and data handling.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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Building a Data-Centric Platform for Generative AI and LLMs at Snowflake

Snowflake

When asked what trends are driving data and AI , I explained two broad themes: The first is seeing more models and algorithms getting productionized and rolled out in interactive ways to the end user. Figure 1: Visual Question Answering Challenge data types and results.

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Data Engineering Weekly #207

Data Engineering Weekly

[link] QuantumBlack: Solving data quality for gen AI applications Unstructured data processing is a top priority for enterprises that want to harness the power of GenAI. It brings challenges in data processing and quality, but what data quality means in unstructured data is a top question for every organization.

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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.