Artwork

Indhold leveret af The Data Flowcast. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Data Flowcast eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !

The AI-Ready Pipeline: Reimagining Airflow at Veyer® Logistics with Anu Pabla

23:21
 
Del
 

Manage episode 488313701 series 2948506
Indhold leveret af The Data Flowcast. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Data Flowcast eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Innovation in orchestration is redefining how engineers approach both traditional ETL pipelines and emerging AI workloads. Understanding how to harness Airflow’s flexibility and observability is essential for teams navigating today’s evolving data landscape.

In this episode, Anu Pabla, Principal Engineer at The ODP Corporation, joins us to discuss her journey from legacy orchestration patterns to AI-native pipelines and why she sees Airflow as the future of AI workload orchestration.

Key Takeaways:

(03:43) Engaging with external technology communities fosters innovation.

(05:05) Mentoring early-career engineers builds confidence in a complex tech landscape.

(07:51) Orchestration patterns continue to evolve with modern data needs.

(08:41) Managing AI workflows requires structured and flexible orchestration.

(10:35) High-quality, meaningful data remains foundational across use cases.

(15:08) Community-driven open source tools offer lasting value.

(16:59) Self-healing systems support both legacy and AI pipelines.

(20:20) Orchestration platforms can drive future AI-native workloads.

Resources Mentioned:

Anu Pabla

https://www.linkedin.com/in/atomicap/

The ODP Corporation

https://www.linkedin.com/company/the-odp-corporation/

The ODP Corporation | Website

https://www.theodpcorp.com/homepage

Apache Airflow

https://airflow.apache.org/

LlamaIndex

https://www.llamaindex.ai/

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

82 episoder

Artwork
iconDel
 
Manage episode 488313701 series 2948506
Indhold leveret af The Data Flowcast. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Data Flowcast eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Innovation in orchestration is redefining how engineers approach both traditional ETL pipelines and emerging AI workloads. Understanding how to harness Airflow’s flexibility and observability is essential for teams navigating today’s evolving data landscape.

In this episode, Anu Pabla, Principal Engineer at The ODP Corporation, joins us to discuss her journey from legacy orchestration patterns to AI-native pipelines and why she sees Airflow as the future of AI workload orchestration.

Key Takeaways:

(03:43) Engaging with external technology communities fosters innovation.

(05:05) Mentoring early-career engineers builds confidence in a complex tech landscape.

(07:51) Orchestration patterns continue to evolve with modern data needs.

(08:41) Managing AI workflows requires structured and flexible orchestration.

(10:35) High-quality, meaningful data remains foundational across use cases.

(15:08) Community-driven open source tools offer lasting value.

(16:59) Self-healing systems support both legacy and AI pipelines.

(20:20) Orchestration platforms can drive future AI-native workloads.

Resources Mentioned:

Anu Pabla

https://www.linkedin.com/in/atomicap/

The ODP Corporation

https://www.linkedin.com/company/the-odp-corporation/

The ODP Corporation | Website

https://www.theodpcorp.com/homepage

Apache Airflow

https://airflow.apache.org/

LlamaIndex

https://www.llamaindex.ai/

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

82 episoder

所有剧集

×
 
Loading …

Velkommen til Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Hurtig referencevejledning

Lyt til dette show, mens du udforsker
Afspil