Data Engineering Podcast

APRIL 8, 2018

Summary Managing an analytics project can be difficult due to the number of systems involved and the need to ensure that new information can be delivered quickly and reliably. That challenge can be met by adopting practices and principles from lean manufacturing and agile software development, and the cross-functional collaboration, feedback loops, and focus on automation in the DevOps movement.

Manufacturing 100

Manufacturing Machine Learning Data Engineering Data Engineer 100

Uber Engineering

APRIL 12, 2018

As the Vice President of Engineering for Uber’s Core Infrastructure group, Matthew Mengerink faces a daunting task. He oversees 350 engineers across four teams tasked with not only maintaining the platform on which 3,500 microservices run, but also figuring out … The post Scaling for Growth: A Q&A with Uber’s VP of Core Infrastructure, Matthew Mengerink appeared first on Uber Engineering Blog.

Engineering 81

Engineering Architecture Cloud Data 81

Zalando Engineering

APRIL 9, 2018

A product manager's insights on customization Personalization is a common term with digital products. But what does it actually mean, why do we do it, and how does it affect the product manager? To illustrate, let me tell a personal story. I have gone to the same hairdresser for 10 years. He has seen a big part of my life, with big changes and evolutions.

Management 52

Management Machine Learning Data Science Designing 52

Zalando Engineering

APRIL 11, 2018

Our experience of The Sprint About two years ago, Jake Knapp , John Zeratsky and Braden Kowitz from Google Ventures published “ The Sprint.” They describe a methodology that helps you answer critical business questions, develop ideas, or tackle problems in just five days, and last year Jake Knapp shared his insights in a fireside chat at Zalando. Last week, we had the chance to see it in action.

Designing 40

Designing Recruitment Building Management 40

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence