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Go vs. Python for Modern Data Workflows: Need Help Deciding?

KDnuggets

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Go vs. Python for Modern Data Workflows: Need Help Deciding?

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI. And move with confidence and trust with built-in governance to address enterprise security needs.

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10 Large Language Model Key Concepts Explained - KDnuggets

KDnuggets

The number of parameters matters when it comes to measuring an LLMs capabilities, but other aspects like the amount and quality of training data, architecture design, and fine-tuning approaches used are likewise important. By subscribing you accept KDnuggets Privacy Policy Leave this field empty if youre human: No, thanks!

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How To Use Airbyte, dbt-teradata, Dagster, and Teradata Vantage™ for Seamless Data Integration

Teradata

Check your inbox each week for our take on data science, business analytics, tech trends, and more. Your personal information will be collected, stored, and processed in accordance with the Teradata Global Privacy Statement. You're officially subscribed to Teradata's Insights.

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Why Every Organization Needs a Data Marketplace

Data Virtualization

Reading Time: 3 minutes Data is often hailed as the most valuable assetbut for many organizations, its still locked behind technical barriers and organizational bottlenecks. Modern data architectures like data lakehouses and cloud-native ecosystems were supposed to solve this, promising centralized access and scalability.

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Taming the Tide: Delivering AI-Ready Data for Financial Services in the Age of Transience

Data Virtualization

From streaming trade data and fraud signals to real-time KYC updates and credit scoring models, the tempo of financial operations has shifted to milliseconds.

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The Lakehouse Isn’t The End Game — Here’s What Comes Next

Data Virtualization

Reading Time: 2 minutes The data lakehouse has emerged as a powerful and popular data architecture, combining the scale of data lakes with the management features of data warehouses. It promises a unified platform for storing and analyzing structured and unstructured data, particularly for.