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The orchestration layer is foundational to building robust AI- and ML-powered data pipelines, especially in complex hybrid enterprise environments. IBM’s partnership with Astronomer reflects a strategic alignment to simplify and scale Airflow-based workflows across industries.
In this episode, we’re joined by IBM’s Senior Product Manager, BJ Adesoji, and Chief Marketing Officer, Ryan Yackel. We discuss how IBM customers are using Airflow in production, the challenges they face at scale and what the new IBM–Astronomer collaboration unlocks.
Key Takeaways:
(03:09) The growing importance of orchestration tools in enterprise environments.
(04:48) How organizations are expanding orchestration beyond traditional use cases.
(05:24) Common patterns across industries adopting orchestration platforms.
(07:16) Why orchestration is essential for supporting business-critical workloads.
(10:00) The role of orchestration in compliance and regulatory processes.
(13:02) Challenges enterprises face when managing orchestration infrastructure.
(14:58) Opportunities to simplify and centralize orchestration at scale.
(19:11) The value of integrating orchestration with broader data toolchains.
(20:54) How AI is shaping the future of orchestrated data workflows.
Resources Mentioned:
BJ Adesoji
https://www.linkedin.com/in/bj-soji/
Ryan Yackel
https://www.linkedin.com/in/ryanyackel/
IBM | LinkedIn
https://www.linkedin.com/company/databand-ai/
IBM Databand
https://www.ibm.com/products/databand
IBM DataStage
https://www.ibm.com/products/datastage
IBM watsonx.governance
https://www.ibm.com/products/watsonx-governance
IBM Knowledge Catalog
https://www.ibm.com/products/knowledge-catalog
Apache Airflow
https://airflow.apache.org/
watsonx Orchestrate
https://www.ibm.com/products/watsonx-orchestrate
Domino
https://domino.ai/
Astronomer
https://www.astronomer.io/
Snowflake
https://www.snowflake.com/en/
dbt Labs
https://www.getdbt.com/
Amazon SageMaker
https://aws.amazon.com/sagemaker/
Cloudera
https://www.cloudera.com/
MongoDB
https://www.mongodb.com/
https://www.astronomer.io/events/roadshow/london/
https://www.astronomer.io/events/roadshow/new-york/
https://www.astronomer.io/events/roadshow/sydney/
https://www.astronomer.io/events/roadshow/san-francisco/
https://www.astronomer.io/events/roadshow/chicago/
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
5
2020 ratings
The orchestration layer is foundational to building robust AI- and ML-powered data pipelines, especially in complex hybrid enterprise environments. IBM’s partnership with Astronomer reflects a strategic alignment to simplify and scale Airflow-based workflows across industries.
In this episode, we’re joined by IBM’s Senior Product Manager, BJ Adesoji, and Chief Marketing Officer, Ryan Yackel. We discuss how IBM customers are using Airflow in production, the challenges they face at scale and what the new IBM–Astronomer collaboration unlocks.
Key Takeaways:
(03:09) The growing importance of orchestration tools in enterprise environments.
(04:48) How organizations are expanding orchestration beyond traditional use cases.
(05:24) Common patterns across industries adopting orchestration platforms.
(07:16) Why orchestration is essential for supporting business-critical workloads.
(10:00) The role of orchestration in compliance and regulatory processes.
(13:02) Challenges enterprises face when managing orchestration infrastructure.
(14:58) Opportunities to simplify and centralize orchestration at scale.
(19:11) The value of integrating orchestration with broader data toolchains.
(20:54) How AI is shaping the future of orchestrated data workflows.
Resources Mentioned:
BJ Adesoji
https://www.linkedin.com/in/bj-soji/
Ryan Yackel
https://www.linkedin.com/in/ryanyackel/
IBM | LinkedIn
https://www.linkedin.com/company/databand-ai/
IBM Databand
https://www.ibm.com/products/databand
IBM DataStage
https://www.ibm.com/products/datastage
IBM watsonx.governance
https://www.ibm.com/products/watsonx-governance
IBM Knowledge Catalog
https://www.ibm.com/products/knowledge-catalog
Apache Airflow
https://airflow.apache.org/
watsonx Orchestrate
https://www.ibm.com/products/watsonx-orchestrate
Domino
https://domino.ai/
Astronomer
https://www.astronomer.io/
Snowflake
https://www.snowflake.com/en/
dbt Labs
https://www.getdbt.com/
Amazon SageMaker
https://aws.amazon.com/sagemaker/
Cloudera
https://www.cloudera.com/
MongoDB
https://www.mongodb.com/
https://www.astronomer.io/events/roadshow/london/
https://www.astronomer.io/events/roadshow/new-york/
https://www.astronomer.io/events/roadshow/sydney/
https://www.astronomer.io/events/roadshow/san-francisco/
https://www.astronomer.io/events/roadshow/chicago/
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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