January 21, 2019

Building Enterprise Big Data Systems At LEGO

48 minutes

Summary

Building internal expertise around big data in a large organization is a major competitive advantage. However, it can be a difficult process due to compliance needs and the need to scale globally on day one. In this episode Jesper Søgaard and Keld Antonsen share the story of starting and growing the big data group at LEGO. They discuss the challenges of being at global scale from the start, hiring and training talented engineers, prototyping and deploying new systems in the cloud, and what they have learned in the process. This is a useful conversation for engineers, managers, and leadership who are interested in building enterprise big data systems.

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management

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Your host is Tobias Macey and today I’m interviewing Keld Antonsen and Jesper Soegaard about the data infrastructure and analytics that powers LEGO

Interview

Introduction

How did you get involved in the area of data management?

My understanding is that the big data group at LEGO is a fairly recent development. Can you share the story of how it got started?

What kinds of data practices were in place prior to starting a dedicated group for managing the organization’s data?

What was the transition process like, migrating data silos into a uniformly managed platform?

What are the biggest data challenges that you face at LEGO?

What are some of the most critical sources and types of data that you are managing?

What are the main components of the data infrastructure that you have built to support the organizations analytical needs?

What are some of the technologies that you have found to be most useful?

Which have been the most problematic?

What does the team structure look like for the data services at LEGO?

Does that reflect in the types/numbers of systems that you support?

What types of testing, monitoring, and metrics do you use to ensure the health of the systems you support?

What have been some of the most interesting, challenging, or useful lessons that you have learned while building and maintaining the data platforms at LEGO?

How have the data systems at Lego evolved over recent years as new technologies and techniques have been developed?

How does the global nature of the LEGO business influence the design strategies and technology choices for your platform?

What are you most excited for in the coming year?

Contact Info

Jesper

Keld

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

LEGO Group

ERP (Enterprise Resource Planning)

Predictive Analytics

Prescriptive Analytics

Hadoop

Center Of Excellence

Continuous Integration

Spark

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