ETL
AssessTechniques
Extract, Transform, Load pipelines that move data into warehouses and other analytics systems.
Why it's here
Placed in Assess: 2 article(s) of evidence from 1 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 31%.
Evidence (2)
- 7The New Stack·7/14/2026researchIBM Misses Earnings as Enterprise AI Spend Reprioritizes Budgets
IBM cut its second-quarter outlook after customers shifted spending toward AI-related infrastructure such as servers, storage, and memory. CEO Arvind Krishna said the company underestimated how quickly clients would reprioritize capex, causing several large deals to slip.
- 6The New Stack·7/7/2026researchWhy AI agents fail on invisible organizational data
The article argues that AI agents struggle not because visible enterprise data is missing, but because the reasoning behind decisions is usually absent from systems of record. It highlights how CRM, ERP, HRIS, data warehouses, and ETL pipelines preserve state but not the context, exceptions, and human judgment needed for reliable cross-system decisions.