Data orchestration and machine learning are shaping how organizations handle massive datasets and drive customer-focused strategies. Tools like Apache Airflow are central to this transformation. In this episode, Vasyl Vasyuta, R&D Team Leader at Optimove, joins us to discuss how his team leverages Airflow to optimize data processing, orchestrate machine learning models and create personalized customer experiences.

Key Takeaways:



(01:59 ) Optimove tailors marketing notifications with personalized customer journeys.

(04:25 ) Airflow orchestrates Snowflake procedures for massive datasets.

(05:11 ) DAGs manage workflows with branching and replay plugins.

(05:41 ) The "Joystick" plugin enables seamless data replays.

(09:33 ) Airflow supports MLOps for customer data grouping.

(11:15 ) Machine learning predicts customer behavior for better campaigns.

(13:20 ) Thousands of DAGs run every five minutes for data processing.

(15:36 ) Custom versioning allows rollbacks and gradual rollouts.

(18:00 ) Airflow logs enhance operational observability.

(23:00 ) DAG versioning in Airflow 3.0 could boost efficiency.

Resources Mentioned:

Vasyl Vasyuta -

https://www.linkedin.com/in/vasyl-vasyuta-3270b54a/

Optimove -

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

Apache Airflow -

https://airflow.apache.org/

Snowflake -

https://www.snowflake.com/

Datadog -

https://www.datadoghq.com/

Apache Airflow Survey -

https://astronomer.typeform.com/airflowsurvey24

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#AI #Automation #Airflow #MachineLearning