DBTB INT Gregory Stewart r
summary
Algorithms are far more powerful than five years ago, pushing some problems into solvable territory while many real problems remain beyond current technical means. Examples include rapid progress toward self-driving cars and the persistent difficulty of spotting employees likely to leave and exfiltrate data — easy to state, hard to detect. Sentiment analysis is only one small piece of larger systems. The key differentiator is imagination: seeing raw metrics as representations of other phenomena and inventing new signals.
AI-written summary · about
related talks
49mdbt: A Software Engineering Approach To The Analytics Workflow
47mData Analytics: Realizing the Full Potential
57mBACK TO THE FUTURE: EMERGING TRENDS IN DATA ENGINEERING
37mData Poker not Data Chess - thinking in Bets for Data Teams
12mTechTalk #1: Big Data challenges in the turbulent year 2022
23mDelivering Modern Data Stacks With dbt to Operationalise Analytics
27mDataEngBytes 2023 - BRI-T1-07 - Joe Reis
49mSilja Märdla | Data Track | Compass AI & Data Summit 2025
