Improving end-to-end cross-team visibility with data lineage. Open Lineage + Dataplex
As organizations scale their data platforms, complexity grows rapidly. Datasets multiply, pipelines expand, and teams specialize. Over time, a critical gap appears: no clear visibility into how data moves, changes, and impacts downstream systems.
In many organizations, this creates two closely connected but very different worlds.
On one side are platform teams — DevOps engineers and data engineers responsible for building and operating the data platform.
On the other side are analytics teams — analysts and data scientists who rely on that platform to produce dashboards, reports, and machine learning models.
As the platform grows, more teams depend on the same datasets and pipelines, but the connections between them become harder to see.
This lack of visibility creates real business risks.
When data issues occur, teams struggle to answer basic questions:
🔶 Where did this data come from?
🔶 Which pipelines produced it?
🔶 Who owns the process?
🔶 What reports, dashboards, or models are affected?
Without clear lineage, even small data problems can turn into major operational incidents.
Data lineage provides the missing visibility layer. It allows organizations to trace data across pipelines, understand dependencies between teams, and quickly assess the impact of changes or failures.
However, many data tools generate lineage metadata in different formats and models, making it difficult for governance platforms to unify and interpret this information.
This is where OpenLineage comes in.
OpenLineage introduces an open standard for lineage and metadata, creating a common language between data processing systems and governance tools. With native integrations for major processing engines (Spark, Airflow, Flink) and clients for Java, Python, and soon Go, it already powers a broad ecosystem.
In this webinar, we’ll explore how OpenLineage and Google Dataplex work together to improve visibility, governance, and trust in modern data platforms.
You will learn:
🔅 Why data lineage is foundational for scalable analytics and AI iniciatives
🔅 How open standards like OpenLineage reduce dependency on proprietary metadata models
🔅 How OpenLineage integrates with Google Cloud and Dataplex
🔅 How a standards‑based lineage layer supports architectural evolution without constant rework
🔅 What’s next for the OpenLineage ecosystem and community
Join us to learn how to build a trusted, AI‑ready data platform on Google Cloud, powered by open standards and enterprise‑grade governance.
When: May 21, 4 pm CET | 10 am EST | 8.30 PM IST
👉 Recording available for registered participants
Duration: 1h, Online on Zoom
Meet the Speakers:
Tomasz Nazarewicz
Lead Data Engineer, Xebia