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World Congress 2024 • Aug 20, 2024 • Session details

Empowering Retail Through Applied Machine Learning

Christoph Fassbach , Daniel Rohr

How did Aldi South deploy automated ML models across 7,000 stores in just nine months? Unpack the hub-and-spoke cloud architecture powering their digital supply chain transformation.

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#1 about 2 min

Global scale and operational footprint of Aldi

How massive transaction volumes across international territories necessitate systemic retail data strategies.

#2 about 3 min

Establishing a dedicated data and analytics organization

Creating a centralized unit with robust support functions rapidly scales operational analytics.

#3 about 3 min

Core data lake environment and infrastructure requirements

Choosing a simplified cloud blueprint minimizes maintenance overhead for foundational orchestration pipelines.

#4 about 1 min

Implementing isolated data environments with satellite architecture

Providing independent core platform clones prevents computational resource contention among discrete teams.

#5 about 2 min

Structuring data flow using a medallion architecture

Progressing records through raw, staged, and business layers securely tracks vital data lineage.

#6 about 2 min

Managing information interchange via central hub nodes

Restricting lateral interconnectivity reduces physical network complexity by routing all payloads centrally.

#7 about 4 min

Optimizing non-food retail lifecycles with intelligent planning

Integrating demand forecasting and automated allocation limits excess stock throughout seasonal merchandise drops.

#8 about 4 min

Applying the satellite architecture for machine learning isolation

Centralizing shared feature engineering minimizes duplicate code and ensures consistency across isolated predictive use cases.

#9 about 2 min

Utilizing specific tooling for continuous integration and modeling

Integrating version control constraints and experiment tracking establishes foundational quality standards across modeling pipelines.

#10 about 3 min

Structuring agile data science teams for rapid deployment

Accelerating framework iteration cycles enables production readiness for complex retail predictive solutions within months.

Matching moments

58 sec

Real-world application of MLOps architectural patterns at Wayfair

Bas Geerdink · LIVE

2:18 min

Introduction to data science applications in the retail sector

Julian Joseph · LIVE

5:10 min

Establishing infrastructure for high-volume enterprise retail

Niklas Blumenthal Niklas Blumenthal +1 · World Congress 2025

6:34 min

Commercial applications of modern artificial intelligence and machine learning

Kris Howard · LIVE

1:47 min

Solving supermarket navigation through retail hackathons

Michael Koitz · Coffee With Developers

4:18 min

Exploring the big data and machine learning portfolio

Qiyang Duan · LIVE

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