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Streamlining AI and ML Operations at IBM with BJ Adesoji and Ryan Yackel

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Manage episode 486931026 series 2948506
Content provided by The Data Flowcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Data Flowcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

  continue reading

59 episodes

Artwork
iconShare
 
Manage episode 486931026 series 2948506
Content provided by The Data Flowcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Data Flowcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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

  continue reading

59 episodes

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