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Fall 2026
Data Management for Data Science
COMPSCI 574 introduces data management principles, covering relational and NoSQL databases, ETL processes, and language model adaptation.
Recorded instructors · Fall 2026 Meena Syamkumar
Summary
Lectures are large, with a median of 144 enrolled students in the recorded sections.
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↗ average GPA
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Prerequisites
Course mapCOMP SCI 320, 400, or graduate/professional standing
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Professors
Fall 2026Historical instructors & teaching patterns
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Calendar & sections
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| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 144 / 175 | 0 |
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Student experience
the class
An introduction to the principles and practices of managing and exploring different kinds of data. Work with both relational databases and Not only SQL (NoSQL) databases to organize and analyze structured, semi-structured, and unstructured data. Write basic queries, forecast time-series data, and evaluate data quality and patterns through exploratory data analysis. Explore data cleaning techniques such as interpolation and imputation, to address missing or inconsistent values. Apply data engineering techniques, including data pipelines, data warehouses, and processes for moving and transforming data using Extract-Transform-Load (ETL) and Extract-Load-Transform (ELT). Learn how modern language models can be adapted using contextual information from custom datasets and strengthened with techniques that incorporate external knowledge sources.
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UW–Madison
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Data Management for Data Science
Recorded 2026-09-07Raw records
[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:266:027413",
"course_id": "COMPSCI 574",
"course_uid": "course_e2127d774d1519c358b75a95",
"term_id": "1272",
"source_course_id": "027413",
"source_subject_id": "266",
"title": "Data Management for Data Science",
"credits_min": 3,
"credits_max": 3,
"typically_offered": "Not Applicable"
}
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Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "902aa9ae82ccb54ddfa66322c374cf37062971c0f6400b816d5c8ebb51c36d9f",
"requirements_status": "needs_review",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}