Mastering Data Orchestration with Airflow at M Science with Ben Tallman

Mastering the flow of data is essential for driving innovation and efficiency in today’s competitive landscape. In this episode, we explore the evolution of data orchestration and the pivotal role of Apache Airflow in modern data workflows.

Ben Tallman, Chief Technology Officer at M Science, joins us and shares his extensive experience with Airflow, detailing its early adoption, evolution and the profound impact it has had on data engineering practices. His insights reveal how leveraging Airflow can streamline complex data processes, enhance observability and ultimately drive business success.

Key Takeaways:

(02:31) Benjamin’s journey with Airflow and its early adoption.

(05:36) The transition from legacy schedulers to Airflow at Apigee and later Google.

(08:52) The challenges and benefits of running production-grade Airflow instances.

(10:46) How Airflow facilitates the management of large-scale data at M Science.

(11:56) The importance of reducing time to value for customers using data products.

(13:32) Airflow’s role in ensuring observability and reliability in data workflows.

(17:00) Managing petabytes of data and billions of records efficiently.

(19:08) Integration of various data sources and ensuring data product quality.

(20:04) Leveraging Airflow for data observability and reducing time to value.

(22:04) Benjamin’s vision for the future development of Airflow, including audit trails for variables.

Resources Mentioned:

• Ben Tallman
• M Science
• Apache Airflow
• Astronomer
• Databricks
• Snowflake

Thanks for listening to The Data Flowcast: Mastering Airflow for Data Engineering & 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