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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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How Financial Services Institutions Should Think About Unstructured Data

Snowflake

Being able to leverage unstructured data is a critical part of an effective data strategy for 2025 and beyond. Having a solid data strategy with a platform that can support both structured and unstructured data. Parse data: What does analyzing unstructured data look like?

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

Unified data access, strong governance and robust security combined with technical expertise and a clear understanding of business objectives will be essential.” Financial services organizations need a modern data platform that allows them to anonymize data and share it without moving or copying it or risking the exposure of PII.

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Snowflake Cortex Search: State-of-the-Art Hybrid Search for RAG Applications

Snowflake

Snowflake Cortex Search, a fully managed search service for documents and other unstructured data, is now in public preview. Solving the challenges of building high-quality RAG applications From the beginning, Snowflake’s mission has been to empower customers to extract more value from their data.

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Data Trends 2024: Strategies for an AI-Ready Data Foundation

Snowflake

We saw that collectively, organizations are definitely preparing their data to be used more effectively with powerful, new AI technologies. The most marked finding was around governance. Strong data governance is essential to meet security and compliance obligations, but it is often regarded as a hindrance.

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Agents of Change: Navigating 2025 with AI and Data Innovation

Data Engineering Weekly

Data engineers, too, face an evolving landscape with a heightened focus on unstructured data. The challenge lies in harnessing this data to drive new insights and efficiencies.

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Data Integrity for AI: What’s Old is New Again

Precisely

(Not to mention the crazy stories about Gen AI making up answers without the data to back it up!) Are we allowed to use all the data, or are there copyright or privacy concerns? These are all big questions about the accessibility, quality, and governance of data being used by AI solutions today.