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Integrating DuckDB & Python: An Analytics Guide

KDnuggets

By Josep Ferrer , KDnuggets AI Content Specialist on June 10, 2025 in Python Image by Author DuckDB is a fast, in-process analytical database designed for modern data analysis. Its tight integration with Python and R makes it ideal for interactive data analysis. EXCLUDE, REPLACE, and ALL) to simplify query writing.

Python 293
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Why You Need RAG to Stay Relevant as a Data Scientist

KDnuggets

By Nate Rosidi , KDnuggets Market Trends & SQL Content Specialist on June 11, 2025 in Language Models Image by Author | Canva If you work in a data-related field, you should update yourself regularly. Data scientists use different tools for tasks like data visualization, data modeling, and even warehouse systems.

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Introducing Agent Bricks: Auto-Optimized Agents Using Your Data

databricks

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data! Agent Bricks is now available in beta.

Analytics 237
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Mosaic AI Announcements at Data + AI Summit 2025

databricks

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

AI 130
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How To Create An Aggregation Pipeline In MongoDB

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction MongoDB is a free open-source No-SQL document database. The post How To Create An Aggregation Pipeline In MongoDB appeared first on Analytics Vidhya.

SQL 319
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Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning Blog

SQL is one of the key languages widely used across businesses, and it requires an understanding of databases and table metadata. This can be overwhelming for nontechnical users who lack proficiency in SQL. This application allows users to ask questions in natural language and then generates a SQL query for the users request.

SQL 116
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Why using Infrastructure as Code for developing Cloud-based Data Warehouse Systems?

Data Science Blog

So why using IaC for Cloud Data Infrastructures? For Data Warehouse Systems that often require powerful (and expensive) computing resources, this level of control can translate into significant cost savings. This brings reliability to data ETL (Extract, Transform, Load) processes, query performances, and other critical data operations.