The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

The Role of Airflow in Finance Transformation at Etraveli Group with Mihir Samant

Transforming bottlenecked finance processes into streamlined, automated systems requires the right tools and a forward-thinking approach. In this episode, Mihir Samant, Senior Data Analyst at Etraveli Group, joins us to share how his team leverages Airflow to revolutionize finance automation. With extensive experience in data workflows and a passion for open-source tools, Mihir provides valuable insights into building efficient, scalable systems. We explore the transformative power of Airflow in automating workflows and enhancing data orchestration within the finance domain. Key Takeaways:(02:14) Etraveli Group specializes in selling affordable flight tickets and ancillary services.(03:56) Mihir’s finance automation team uses Airflow to tackle month-end bottlenecks.(06:00) Airflow's flexibility enables end-to-end automation for finance workflows.(07:00) Open-source Airflow tools offer cost-effective solutions for new teams.(08:46) Sensors and dynamic DAGs are pivotal features for optimizing tasks.(13:30) GitSync simplifies development by syncing environments seamlessly.(16:27) Plans include integrating Databricks for more advanced data handling.(17:58) Airflow and Databricks offer multiple flexible methods to trigger workflows and execute SQL queries seamlessly.Resources Mentioned:Mihir Samant -https://www.linkedin.com/in/misamant/?originalSubdomain=caEtraveli Group -https://www.linkedin.com/company/etraveli-group/Apache Airflow -https://airflow.apache.org/Docker -https://www.docker.com/Databricks -https://www.databricks.com/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

Inside Ford’s Data Transformation: Advanced Orchestration Strategies with Vasantha Kosuri-Marshall

Data engineering is entering a new era, where orchestration and automation are redefining how large-scale projects operate. This episode features Vasantha Kosuri-Marshall, Data and ML Ops Engineer at Ford Motor Company. Vasantha shares her expertise in managing complex data pipelines. She takes us through Ford's transition to cloud platforms, the adoption of Airflow and the intricate challenges of orchestrating data in a diverse environment.Key Takeaways:(03:10) Vasantha’s transition to the Advanced Driving Assist Systems team at Ford.(05:42) Early adoption of Airflow to orchestrate complex data pipelines.(09:29) Ford's move from on-premise data solutions to Google Cloud Platform.(12:03) The importance of Airflow's scheduling capabilities for efficient data management.(16:12) Using Kubernetes to scale Airflow for large-scale data processing.(19:59) Vasantha’s experience in overcoming challenges with legacy orchestration tools.(22:22) Integration of data engineering and data science pipelines at Ford.(28:03) How deferrable operators in Airflow improve performance and save costs.(32:12) Vasantha’s insights into tuning Airflow properties for thousands of DAGs.(36:09) The significance of monitoring and observability in managing Airflow instances.Resources Mentioned:Vasantha Kosuri-Marshall -https://www.linkedin.com/in/vasantha-kosuri-marshall-0b0aab188/Apache Airflow -https://airflow.apache.org/Google Cloud Platform (GCP) - https://cloud.google.com/Ford Motor Company | LinkedIn -https://www.linkedin.com/company/ford-motor-company/Ford Motor Company | Website -https://www.ford.com/Astronomer -https://www.astronomer.io/Apache Airflow Survey -https://astronomer.typeform.com/airflowsurvey24Thanks 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

Powering Finance With Advanced Data Solutions at Ramp with Ryan Delgado

Data is the backbone of every modern business, but unlocking its full potential requires the right tools and strategies. In this episode, Ryan Delgado, Director of Engineering at Ramp, joins us to explore how innovative data platforms can transform business operations and fuel growth. He shares insights on integrating Apache Airflow, optimizing data workflows and leveraging analytics to enhance customer experiences.Key Takeaways:(01:52) Data is the lifeblood of Ramp, touching every vertical in the company.(03:18) Ramp’s data platform team enables high-velocity scaling through tailored tools.(05:27) Airflow powers Ramp’s enterprise data warehouse integrations for advanced analytics.(07:55) Centralizing data in Snowflake simplifies storage and analytics pipelines.(12:08) Machine learning models at Ramp integrate seamlessly with Airflow for operational excellence.(14:11) Leveraging Airflow datasets eliminates inefficiencies in DAG dependencies.(17:22) Platforms evolve from solving narrow business problems to scaling organizationally.(18:55) ClickHouse enhances Ramp’s OLAP capabilities with 100x performance improvements.(19:47) Ramp’s OLAP platform improves performance by reducing joins and leveraging ClickHouse.(21:46) Ryan envisions a lighter-weight, more Python-native future for Airflow.Resources Mentioned:Ryan Delgado - https://www.linkedin.com/in/ryan-delgado-69544568/Ramp - https://www.linkedin.com/company/ramp/Apache Airflow - https://airflow.apache.org/Snowflake - https://www.snowflake.com/ClickHouse -https://clickhouse.com/dbt -https://www.getdbt.com/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

Exploring the Power of Airflow 3 at Astronomer with Amogh Desai

What does it take to go from fixing a broken link to becoming a committer for one of the world’s leading open-source projects? Amogh Desai, Senior Software Engineer at Astronomer, takes us through his journey with Apache Airflow. From small contributions to building meaningful connections in the open-source community, Amogh’s story provides actionable insights for anyone on the cusp of their open-source journey.Key Takeaways:(02:09) Building data engineering platforms at Cloudera with Kubernetes.(04:00) Brainstorming led to contributing to Apache Airflow.(05:17) Starting small with link fixes, progressing to Breeze development.(07:00) Becoming a committer for Apache Airflow in September 2023.(09:51) The steep learning curve for contributing to Airflow.(16:30) Using GitHub’s “good-first-issue” label to get started.(18:15) Setting up a development environment with Breeze.(22:00) Open-source contributions enhance your resume and career.(24:51) Amogh’s advice: Start small and stay consistent.(28:12) Engage with the community via Slack, email lists and meetups.Resources Mentioned:Amogh Desai -https://www.linkedin.com/in/amogh-desai-385141157/?originalSubdomain=in%20%20https://www.linkedin.com/company/astronomer/Astronomer -https://www.linkedin.com/company/astronomer/Apache Airflow GitHub Repository -https://github.com/apache/airflowContributors Quick Guide -https://github.com/apache/airflow/blob/main/CONTRIBUTING.rstBreeze Development Tool -https://github.com/apache/airflow/tree/main/dev/breezeThanks 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

Using Airflow To Power Machine Learning Pipelines at Optimove with Vasyl Vasyuta

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/airflowsurvey24Thanks 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