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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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Your Generative AI LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers

DataKitchen

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure.

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Data governance in the age of generative AI

AWS Big Data

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

According to a recent report by InformationWeek , enterprises with a strong AI strategy are 3 times more likely to report above-average data integration success. Additionally, a study by McKinsey found that organisations leveraging AI in data integration can achieve an average improvement of 20% in data quality.

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Drive Growth with Data-Driven Strategies: Introducing Zenia Graph’s Salesforce Accelerator

Ontotext

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.

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Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Clean data in, clean analytics out.

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Ontotext’s Semantic Approach Towards LLM, Better Data and Content Management: An Interview with Doug Kimball and Atanas Kiryakov

Ontotext

The rich semantics built into our knowledge graph allow you to gain new insights, detect patterns and identify relationships that other data management techniques can’t deliver. Plus, because knowledge graphs can combine data from various sources, including structured and unstructured data, you get a more holistic view of the data.