March 2022 Summaries

Data lineage is an essential process that traces the relationships among datasets within an organization's data ecosystem, offering a comprehensive view of data origins, transformations, and destinations. This visibility is crucial for troubleshooting, decision-making, and ensuring compliance, as it allows for a clear understanding of data flow and dependencies, which is vital in today's complex and distributed data environments. Data lineage complements data classification by categorizing data based on sensitivity and importance, enhancing security and compliance efforts. Tools like OpenLineage and Marquez provide standardized frameworks for capturing and querying lineage metadata, enabling organizations to manage data lifecycle, troubleshoot pipeline issues, and maintain data integrity more effectively. Unlike task hierarchy views in tools like Airflow, which show task dependencies, data lineage maps dataset-to-dataset relationships, making it easier to identify and resolve issues that span multiple systems or teams. Companies like Astronomer integrate Airflow and OpenLineage to provide enhanced visibility into the data ecosystem, allowing for faster resolution of data outages, better understanding of cross-team dependencies, and improved data quality and performance monitoring.

Astronomer has acquired Datakin, a data lineage tool developed by the founders of the OpenLineage and Marquez open-source projects, to enhance the visibility and operational awareness of data ecosystems. This acquisition aims to integrate Datakin's capabilities into Astronomer's modern data orchestration platform, powered by Apache Airflow, enabling organizations to trace and visualize data lineage through pipelines and enhance their ability to manage reliable data ecosystems. Datakin provides end-to-end operational visibility, allowing teams to resolve and prevent data issues by tracing data lineage and tracking changes over time. Founded by Laurent Paris and Julien Le Dem, Datakin is built around the open-source frameworks OpenLineage and Marquez, offering a comprehensive view of distributed data systems. Astronomer, founded in 2018 and a steward of the Airflow project, provides a platform that empowers data teams to build, run, and observe data pipelines with a focus on developer productivity, observability, and flexibility. The collaboration between Astronomer and Datakin promises to bring new product developments as they enhance data orchestration capabilities.

Astronomer, under the leadership of CEO Joe Otto, has been instrumental in enhancing Apache Airflow, an open-source platform favored by data engineers for orchestrating complex workflows. Initially focusing on supporting and improving Airflow, Astronomer prioritized the open-source community over commercial interests, a strategy that attracted significant investment from notable venture capitalists and leaders like Tim Guleri of Sierra Ventures and Scott Yara of Sutter Hill Ventures. Their efforts culminated in the successful release of Airflow 2.0, significantly boosting its global usage. As Astronomer continues to grow, with a team expansion and increasing monthly downloads, it plans to integrate data lineage into its offerings, exemplified by its acquisition of Datakin, to further solidify its role in the data ecosystem. The company's commitment to Airflow and its broader vision for data orchestration continue to drive its mission to provide reliable and innovative solutions for businesses reliant on data pipelines.

Astronomer has made significant advancements, as reported by TechCrunch's Christine Hall, with the acquisition of Datakin, a data lineage tool, and the successful completion of a Series C funding round. Since its last feature in 2017, Astronomer has grown substantially, now serving customers in over 35 countries as a global remote-first company. Founded in 2018, Astronomer provides a modern data orchestration platform called Astro, powered by Airflow, which supports data engineers, scientists, and analysts in constructing, managing, and monitoring pipelines-as-code.

The text highlights how Astronomer leverages Apache Airflow® to empower data teams by providing a seamless experience in data orchestration, catering to the varied needs of data practitioners and their leaders. Steven Hillion, Astronomer's VP of Data, explains how his team uses Airflow to manage data pipelines and analytics, which in turn provides crucial business insights that enhance operations across the organization. Data leaders face pressures to deliver beyond static insights, integrating sophisticated machine learning and analytics into everyday operations, while avoiding common pitfalls like engaging in overly innovative projects at the expense of essential business metrics. Apache Airflow® is praised for its flexibility, adaptability, and ability to integrate with diverse technologies, serving as a critical tool in empowering analysts and fostering productivity. Hillion emphasizes the platform's role in enabling efficient data processing and experimentation with predictive models, illustrating its value through personal experience with Astronomer's Astro platform, which facilitates rapid deployment and execution of data-driven tasks.

Airflow Summit 2022 is a major community-driven event focused on Apache Airflow, set to take place from May 23-27, 2022, as a free online gathering with additional in-person events in various cities. With over 1,900 contributors and significant industry recognition, Airflow is a leading data orchestration tool used by organizations of all sizes. The summit will feature five days of sessions offering insights and knowledge from top data experts and practitioners worldwide, with participation from notable companies such as Pinterest, Societe Generale, PayPal, and Wise. Astronomer, an active community member, is sponsoring and co-organizing the event, which aims to surpass the success of the previous year's conference that featured more than 50 sessions and attracted 10,000 attendees. Participants are encouraged to register to enhance their Airflow skills and engage with the global data community.