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Building the Future with Data Engineering: Uma Uppin on Crafting Scalable Infrastructure, Tracking Business Metrics, and Embracing an AI-Driven World
- Uma Uppin delves into the evolving field of data engineering, exploring how it forms the backbone of data-driven organizations today.
- Uma provides a detailed look at the strategies that enable businesses to turn raw data into actionable insights.
- Critical components of data infrastructure and data quality were defined and the importance of tracking user metrics like acquisition, retention, and churn were explored.
- Data engineering gathers events when a new user onboards a product and tracks their activity on the product and builds pipelines to compute the metrics across various time windows.
- Starting with a data infrastructure and analytics team is advocated, the analytics team can swiftly build pipelines to analyze different stages of the funnel.
- It becomes essential to establish a data engineering function that will build foundational core dimensions and metrics.
- Observability is a vital element in building effective monitoring systems, allowing teams to maintain oversight and respond quickly to issues.
- Two main types of alerting and monitoring systems are identified.
- Organizations can build several key metrics to help them understand a product’s success.
- With AI rapidly advancing, a company’s success will depend on its ability to build and integrate generative AI applications.
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