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Managing Uber’s Data Workflows at Scale

Uber Engineering

At Uber’s scale, thousands of microservices serve millions of rides and deliveries a day, generating more than a hundred petabytes of raw data. Internally, engineering and data teams across the company leverage this data to improve the Uber experience.

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New Fivetran connector streamlines data workflows for real-time insights

ThoughtSpot

The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. And even when we manage to streamline the data workflow, those insights aren’t always accessible to users unfamiliar with antiquated business intelligence tools.

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Introducing WorkflowGuard: The Workflow Governance and Observability System That Oversees over 120,000 Data Workflows

Uber Engineering

Our Data Workflow Platform team introduces WorkflowGuard: a new service to govern executions, prioritize resources, and manage life cycle for repetitive data jobs. Check out how it improved workflow reliability and cost efficiency while bringing more observability to users.

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Scale Unstructured Text Analytics with Batch LLM Inference

Snowflake

And to create significant technology and team efficiencies, organizations need to consider opportunities to integrate LLM pipelines with existing structured data workflows. This unification can also empower data engineers, who already manage structured pipelines, to easily onboard and maintain unstructured data workflows.

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The Emerging Role of AI Data Engineers - The New Strategic Role for AI-Driven Success

Data Engineering Weekly

As large language models (LLMs) and AI agents become indispensable in everything from customer service to autonomous vehicles, the ability to manage, analyze, and optimize unstructured data has become a strategic imperative. Billions of social media posts, hours of video content, and terabytes of sensor data are produced daily.

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5 Hidden Gem Python Libraries for Data Science

KDnuggets

Exploring the not-so-famous data science libraries that can be useful in your data workflow.

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Utilizing Pandas AI for Data Analysis

KDnuggets

Bring the latest AI implementation to Pandas to improve your data workflow.

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