The shift to a unified data platform is reshaping how pharmaceutical companies manage and orchestrate data. Establishing standards across regions and teams ensures scalability and efficiency in handling large-scale analytics.In this episode, <a href="https://www.linkedin.com/in/prusov/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Evgenii Prusov</a>, Senior Data Platform Engineer of <a href="https://www.linkedin.com/company/daiichi-sankyo-europe-gmbh/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Daiichi Sankyo Europe GmbH</a>, joins us to discuss building and scaling a centralized data platform with Airflow and Astronomer.Key Takeaways:00:00 Introduction.02:49 Building a centralized data platform for 15 European countries.05:19 Adopting SaaS to manage Airflow from day one.07:01 Leveraging Airflow for data orchestration across products.08:16 Teaching non-Python users how to work with Airflow is challenging.12:25 Creating a global data community across Europe, the US and Japan.14:04 Monthly calls help share knowledge and align regional teams.15:47 Contributing to the open-source Airflow project as a way to deepen expertise.16:32 Desire for more guidelines, debugging tutorials and testing best practices in Airflow.Resources Mentioned:&nbsp;<a href="https://www.linkedin.com/in/prusov/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Evgenii Prusov</a>https://www.linkedin.com/in/prusov/<a href="https://www.linkedin.com/company/daiichi-sankyo-europe-gmbh/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Daiichi Sankyo Europe GmbH</a> | LinkedInhttps://www.linkedin.com/company/daiichi-sankyo-europe-gmbh/<a href="https://www.daiichi-sankyo.eu" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Daiichi Sankyo Europe GmbH</a> | Websitehttps://www.daiichi-sankyo.eu<a href="https://airflow.apache.org/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Apache Airflow</a>https://airflow.apache.org/<a href="https://www.astronomer.io/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Astronomer</a>https://www.astronomer.io/<a href="https://www.snowflake.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Snowflake</a>https://www.snowflake.com/Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.#AI #Automation #Airflow #MachineLearning

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Overcoming Data Engineering Challenges at Daiichi Sankyo Europe GmbH with Evgenii Prusov

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

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