How does your BI team scale when you go from a startup to €4.5 billion per year? Or when you decide to embrace microservices? Is your data infrastructure ready to do data science, machine learning, and AI, or will you be squashed by the weight of the next buzzword?
Zalando, the top fashion destination in Europe, had to find answers to these questions while also discovering and addressing new problems and challenges. As the company moved from batch ETL to streaming, from precooked reports to data exploration, from dashboards to training algorithms, it questioned its data, its tools, its customers, and even itself. And when Zalando introduced the concept of radical agility, it spawned a few dozen different autonomous teams able to decide the ways they wanted to solve their problems. This led to a lot of creativity but also the need for a shared platform to avoid reinventing the wheel all the time.
Francesco Mucio tells the story of how Zalando went from an old-school BI company to an AI-driven company built on a solid data platform. Much like that other similarly named fashion icon Derek Zoolander, Zalando managed to evolve to a modern “ambiturner” data architecture able to satisfy standard reporting, data exploration, and machine learning. Its top goal was to provide the tools to solve business problems and not to get lost in trivial technical issues. Scaling the data infrastructure meant scaling the amount of data that the company ingests, processes, and serves daily; scaling the number of users from a few thousand internal users to millions of customers; scaling the type of users, including analysts, scientists, and even machines; and scaling the number of use cases, from simple reports to complex models, from real-time analysis to recommendation systems. And the company had to make the platform more than three times bigger. Francesco shares what Zalando learned in the process and the challenges that still lie ahead.
Francesco Mucio is a data consultant. The first time Francesco met the word data, it was just the plural of datum, and now he’s building a small consulting firm to help organizations to avoid or solve some of the problems he’s seen in the past. He likes to draw data models and optimize queries. He spends his free time with his daughter, who, for some reason, speaks four languages.
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