Session: Achieving near real-time compliance at scale: How Uber manages sensitive data across an exabyte of global systems

Ajit Panda, Head of Data Security & Governance @ Uber

Uber has an exabyte of data across various systems like data lake, datastores backing up critical apps, and unstructured data lying around various drives. At the same time, Uber operates across the globe needing to ensure they comply with regulations as mandated by the countries/states it operates in.

In the last few years, Uber has come a long way from being reactive and spending a huge amount of time and resources to rewrite and risk reliability issues to being compliant near real-time. This is a huge turnaround on how compliance is being enforced in the industry.

In this talk, Ajit will focus on how Uber classifies data to identify various types of sensitive information, tools they have built over time to enforce compliance, and fine-grained monitoring.

Want to learn more? Check out these resources from our co-chair Onehouse:

Where & when?

Open Source Data Summit 2024 was held on October 2nd, 2024.

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OSDS is always free and open for all to attend.

What is Open Source Data Summit?

OSDS is a peer-to-peer gathering of data industry professionals, experts, and enthusiasts to explore the dynamic landscape of open source data tools and storage.

The central theme of OSDS revolves around the advantages of open source data products and their pivotal role in modern data ecosystems.

OSDS is the annual peer hub for knowledge exchange that fosters a deeper understanding of open source options and their role in shaping the data-driven future.

Who attends OSDS?

OSDS is attended by data engineers, data architects, developers, DevOps practitioners and managers, and data leadership.

Anyone who is looking for enriched perspectives on open source data tools and practical insights to navigate the evolving data landscape should attend this event.

On October 2nd, 2024 we convened for discussions about:

Benefits of open source data tools
Cost/performance trade-offs
Building data storage solutions
Challenges surrounding open source data tool integration
Solutions for the cost of storing, accessing, and managing data
Data streams and ingestion
Hub-and-spoke data integration models
Choosing the right engine for your workload

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