Category: sql
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Graph RAG vs SQL RAG
Graph RAG vs SQL RAG Evaluating RAGs on graph and SQL databases The post Graph RAG vs SQL RAG appeared first on Towards Data Science. Reinhard Sellmair Go to original source
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A Focused Approach to Learning SQL
A Focused Approach to Learning SQL Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store customer purchases in one table, customer demographics in another, and suppliers in a third table. These tables…
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How to Correctly Apply Limits on the Result in DAX (and SQL)
How to Correctly Apply Limits on the Result in DAX (and SQL) What if the output of a measure mustn’t be above a specific limit? How can we ensure that the total is calculated correctly? This piece is about correctly calculating and summarizing such output. The post How to Correctly Apply Limits on the Result…
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Change-Aware Data Validation with Column-Level Lineage
Change-Aware Data Validation with Column-Level Lineage Data transformation tools like dbt make constructing SQL data pipelines easy and systematic. But even with the added structure and clearly defined data models, pipelines can still become complex, which makes debugging issues and validating changes to data models difficult. The post Change-Aware Data Validation with Column-Level Lineage appeared…
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A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control
A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control Your very own SQL assistant built with Streamlit, SQLite, & CrewAI The post A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control appeared first on Towards Data Science. Alle Sravani Go to original source
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Mastering SQL Window Functions
Mastering SQL Window Functions Understand how to use Window Functions to perform calculations without losing details The post Mastering SQL Window Functions appeared first on Towards Data Science. Eugenia Anello Go to original source
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Are We Watching More Ads Than Content? Analyzing YouTube Sponsor Data
Are We Watching More Ads Than Content? Analyzing YouTube Sponsor Data I’m definitely not the only person who feels that YouTube sponsor segments have become longer and more frequent recently. Sometimes, I watch videos that seem to be trying to sell me something every couple of seconds. On one hand, it’s great that both small and…
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7 Powerful DBeaver Tips and Tricks to Improve Your SQL Workflow
7 Powerful DBeaver Tips and Tricks to Improve Your SQL Workflow DBeaver is the most powerful open-source SQL IDE, but there are several features people don’t know about. In this post, I will share with you several features to speed up your workflow, with zero fluff. I’ve learned these as I’m currently digging deeper into…
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Practical SQL Puzzles That Will Level Up Your Skill
Practical SQL Puzzles That Will Level Up Your Skill There are some Sql patterns that, once you know them, you start seeing them everywhere. The solutions to the puzzles that I will show you today are actually very simple SQL queries, but understanding the concept behind them will surely unlock new solutions to the queries…
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Advanced SQL Techniques for Unstructured Data Handling
Advanced SQL Techniques for Unstructured Data Handling Everything you need to know to get started with text mining Continue reading on Towards Data Science » Jiayan Yin Go to original source
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How to Build an AI Agent for Data Analytics Without Writing SQL
How to Build an AI Agent for Data Analytics Without Writing SQL Create a comprehensive AI agent from the ground up utilizing LangChain and DuckDB Continue reading on Towards Data Science » Chengzhi Zhao Go to original source
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Scaling Statistics: Incremental Standard Deviation in SQL with dbt
Scaling Statistics: Incremental Standard Deviation in SQL with dbt Why scan yesterday’s data when you can increment today’s? Image by the author SQL aggregation functions can be computationally expensive when applied to large datasets. As datasets grow, recalculating metrics over the entire dataset repeatedly becomes inefficient. To address this challenge, incremental aggregation is often employed — a method…
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Measuring Cross-Product Adoption Using dbt_set_similarity
Measuring Cross-Product Adoption Using dbt_set_similarity Enhancing cross-product insights within dbt workflows Introduction For multi-product companies, one critical metric is often what is called “cross-product adoption”. (i.e. understanding how users engage with multiple offerings in a given product portfolio) One measure suggested to calculate cross-product or cross-feature usage in the popular book Hacking Growth [1] is…
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From Prototype to Production: Enhancing LLM Accuracy
From Prototype to Production: Enhancing LLM Accuracy Implementing evaluation frameworks to optimize accuracy in real-world applications Image created by DALL-E 3 Building a prototype for an LLM application is surprisingly straightforward. You can often create a functional first version within just a few hours. This initial prototype will likely provide results that look legitimate and be…
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Query Optimization for Mere Humans in PostgreSQL
Query Optimization for Mere Humans in PostgreSQL PostgreSQL: Query Optimization for Mere Humans Understanding a PostgreSQL execution plan with practical examples Photo by Greg Rakozy on Unsplash Today, users have high expectations for the programs they use. Users expect programs to have amazing features, to be fast, and to consume a reasonable amount of resources. As developers,…