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İçerik The Data Flowcast tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan The Data Flowcast veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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Building Resilient Data Systems for Modern Enterprises at Astrafy with Andrea Bombino

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Manage episode 448897519 series 2948506
İçerik The Data Flowcast tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan The Data Flowcast veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Efficient data orchestration is the backbone of modern analytics and AI-driven workflows. Without the right tools, even the best data can fall short of its potential. In this episode, Andrea Bombino, Co-Founder and Head of Analytics Engineering at Astrafy, shares insights into his team’s approach to optimizing data transformation and orchestration using tools like datasets and Pub/Sub to drive real-time processing. Andrea explains how they leverage Apache Airflow and Google Cloud to power dynamic data workflows.

Key Takeaways:

(01:55) Astrafy helps companies manage data using Google Cloud.

(04:36) Airflow is central to Astrafy’s data engineering efforts.

(07:17) Datasets and Pub/Sub are used for real-time workflows.

(09:59) Pub/Sub links multiple Airflow environments.

(12:40) Datasets eliminate the need for constant monitoring.

(15:22) Airflow updates have improved large-scale data operations.

(18:03) New Airflow API features make dataset updates easier.

(20:45) Real-time orchestration speeds up data processing for clients.

(23:26) Pub/Sub enhances flexibility across cloud environments.

(26:08) Future Airflow features will offer more control over data workflows.

Resources Mentioned:

Andrea Bombino -

https://www.linkedin.com/in/andrea-bombino/

Astrafy -

https://www.linkedin.com/company/astrafy/

Apache Airflow -

https://airflow.apache.org/

Google Cloud -

https://cloud.google.com/

dbt -

https://www.getdbt.com/

Apache Airflow Survey -

https://astronomer.typeform.com/airflowsurvey24

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

  continue reading

37 bölüm

Artwork
iconPaylaş
 
Manage episode 448897519 series 2948506
İçerik The Data Flowcast tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan The Data Flowcast veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Efficient data orchestration is the backbone of modern analytics and AI-driven workflows. Without the right tools, even the best data can fall short of its potential. In this episode, Andrea Bombino, Co-Founder and Head of Analytics Engineering at Astrafy, shares insights into his team’s approach to optimizing data transformation and orchestration using tools like datasets and Pub/Sub to drive real-time processing. Andrea explains how they leverage Apache Airflow and Google Cloud to power dynamic data workflows.

Key Takeaways:

(01:55) Astrafy helps companies manage data using Google Cloud.

(04:36) Airflow is central to Astrafy’s data engineering efforts.

(07:17) Datasets and Pub/Sub are used for real-time workflows.

(09:59) Pub/Sub links multiple Airflow environments.

(12:40) Datasets eliminate the need for constant monitoring.

(15:22) Airflow updates have improved large-scale data operations.

(18:03) New Airflow API features make dataset updates easier.

(20:45) Real-time orchestration speeds up data processing for clients.

(23:26) Pub/Sub enhances flexibility across cloud environments.

(26:08) Future Airflow features will offer more control over data workflows.

Resources Mentioned:

Andrea Bombino -

https://www.linkedin.com/in/andrea-bombino/

Astrafy -

https://www.linkedin.com/company/astrafy/

Apache Airflow -

https://airflow.apache.org/

Google Cloud -

https://cloud.google.com/

dbt -

https://www.getdbt.com/

Apache Airflow Survey -

https://astronomer.typeform.com/airflowsurvey24

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

  continue reading

37 bölüm

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