NLP & ML data-driven decision making: Taming the curriculum beast

Joel Hernandez, CTO @ eLumen

Carlos Rodríguez, Data and Analytics Manager @ MentorMate

Recent advances in Natural Language Processing (NLP) and Machine Learning (ML) created unprecedented opportunities for organizations to leverage heterogeneous data scenarios. We can now draw insights from not only structured data but unstructured ones (text) as well.

eLumen partnered with MentorMate to deliver Data Engineering, NLP, and ML tools that harvest and curate course data and learning outcomes in higher education curriculum improvement. Formerly unstructured data tracked by the eLumen Insights platform now has key metadata and graph relations and can be stored in institutional data lakes that drive insights.

Joel and Carlos will share how eLumen Insights leverages graph DBs, data lake, and ML/NLP technologies to drive data curation and insights in heterogeneous unstructured data scenarios.

Where & when?

Data Stack Summit 2023 was held virtually on April 19, 2023.

What is the cost to attend the virtual sessions?

Data Stack Summit is always free and open for all to attend

What is Data Stack Summit?

Finding ways to efficiently conquer the modern data stack can become infinitely more possible when we’re able to gather together collaboratively as a community and discuss the tools and capabilities desired by future-forward organizations. 

Hear real-world perspectives from long-time data visionaries, data engineers, data and cloud architects, DataOps and DevOps practitioners as they talk through topics like the building blocks of the modern data platform, open source considerations, best practices for impactful data operations, migrations, data observability, and tuning data pipelines for performance at scale.

Who comes to Data Stack Summit?

Data and cloud architects, data engineers, DevOps practitioners and managers, data and ITOps leaders

Join us for talks around things like:
  • Building blocks of the modern data platform
  • Implementing the modern data platform using open source
  • Deploying the modern data platform using K8s
  • Best practices for data team operations
  • Migrations to modern data platforms
  • Optimizing high-performance big data for future-forward organizations
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