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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. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

What Makes a Data Fabric? Data Fabric’ has reached where ‘Cloud Computing’ and ‘Grid Computing’ once trod. Data Fabric hit the Gartner top ten in 2019. This multiplicity of data leads to the growth silos, which in turns increases the cost of integration. It is a buzzword.

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The Missing Link in Enterprise Data Governance: Metadata

Octopai

We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Enterprise data governance. Metadata in data governance. Metadata is essentially the ‘data about data.’

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

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You Cannot Get to the Moon on a Bike!

Ontotext

Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.