The shift from simple cron jobs to orchestrated AI-powered workflows is reshaping how startups scale. For a small team, these transitions come with unique challenges and big opportunities.In this episode, <a href="https://www.linkedin.com/in/naseemshah/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Naseem Shah</a>, Head of Engineering at <a href="https://www.linkedin.com/company/xena-intelligence/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Xena Intelligence</a>, shares how he built data pipelines from scratch, adopted Apache Airflow and transformed Amazon review analysis with LLMs.Key Takeaways:00:00 Introduction.03:28 The importance of building initial products that support growth and investment.06:16 The process of adopting new tools to improve reliability and efficiency.09:29 Approaches to learning complex technologies through practice and fundamentals.13:57 Trade-offs small teams face when balancing performance and costs.18:40 Using AI-driven approaches to generate insights from large datasets.22:38 How unstructured data can be transformed into actionable information.25:55 Moving from manual tasks to fully automated workflows.28:05 Orchestration as a foundation for scaling advanced use cases.Resources Mentioned:<a href="https://www.linkedin.com/in/naseemshah/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Naseem Shah</a>https://www.linkedin.com/in/naseemshah/<a href="https://www.linkedin.com/company/xena-intelligence/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Xena Intelligence</a> | LinkedInhttps://www.linkedin.com/company/xena-intelligence/<a href="https://xenaintelligence.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Xena Intelligence</a> | Websitehttps://xenaintelligence.com/<a href="https://airflow.apache.org/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Apache Airflow</a>https://airflow.apache.org/<a href="https://cloud.google.com/composer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Google Cloud Composer</a>https://cloud.google.com/composer<a href="https://www.techstars.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Techstars</a>https://www.techstars.com/<a href="https://www.docker.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Docker</a>https://www.docker.com/<a href="https://aws.amazon.com/sqs/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">AWS SQS</a>https://aws.amazon.com/sqs/<a href="https://www.postgresql.org/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">PostgreSQL</a>https://www.postgresql.org/﻿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

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Transforming Data Pipelines at XENA Intelligence with Naseem Shah

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

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