FOUNDATIONS OF DATA MANAGEMENT

Name: FOUNDATIONS OF DATA MANAGEMENT
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Rating: 4.6 (502 reviews)

COMPSCI 784

과목 설명

Foundational concepts in databases and data management. The first part of the course discusses topics on query languages (conjunctive queries, Datalog), their expressivity and complexity of evaluation. The second part studies advanced topics in modern data management, including data streams, massive parallelism, provenance, uncertain data management and privacy. There are no specific course prerequisites. It is strongly encouraged that the students are familiar with databases and relational algebra (COMP SCI 564or equivalent). Knowledge of algorithms, complexity theory and probability will also be helpful.

선수과목

Graduate/professional standing

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

미보고

평점

3.68

-0.92% 과거 데이터 대비

수료율

100%

0.4% 과거 데이터 대비

A 비율

63.64%

3.05% 과거 데이터 대비

학급 규모

-21.12% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

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유사 과목

DATABASE MANAGEMENT SYSTEMS: DESIGN AND IMPLEMENTATION

COMPSCI 564

What a database management system is; different data models currently used to structure the logical view of the database: relational, hierarchical, and network. Hands-on experience with relational and network-based database systems. Implementation techniques for database systems. File organization, query processing, concurrency control, rollback and recovery, integrity and consistency, and view implementation.

TOPICS IN DATABASE MANAGEMENT SYSTEMS

COMPSCI 764

Implementation of database management systems, the impact of new technology on database management systems, back-end database computers, distributed database management systems, concurrency control, and query execution in both distributed and centralized systems, implementation of multiple user views, roll-back and recovery mechanisms, database translation. Students are strongly encouraged to have knowledge of database design (e.g.,COMP SCI 564).

INTRODUCTION TO DATABASES

INFOSYS 322

Introduction to database management systems with a focus on relational databases. Covers designing, creating, populating, managing, and retrieving data from databases. SQL will be used with a focus on querying for business applications and intelligence, data retrieval for summary reports, and data visualization. Offers a brief introduction to non-relational databases for business applications.

DATA EXPLORATION, CLEANING, AND INTEGRATION FOR DATA SCIENCE

COMPSCI 774

Big Data is often said to deal with four Vs: volume, velocity, variety, and veracity. The focus is on variety and veracity challenges, which often arise in data science projects. In many such projects, data is often incorrect, hard to understand, and come from a variety of sources. Data scientists often spend 80% of their effort to explore, clean, and integrate this data, before analysis can be carried out to extract insights. As a result, managing variety and veracity has received significant attention. Study these topics, understand their challenges, and discuss solutions. These solutions often require data management, machine learning, big data scaling, cloud, crowdsourcing, and user interaction techniques. Knowledge of machine learning/AI [COMP SCI 540], databases [COMP SCI 564] and Python [COMP SCI 320] recommended.

INTRODUCTION TO BIG DATA SYSTEMS

COMPSCI 544

Deploy and use distributed systems to store and analyze large datasets. Unstructured and structured approaches to storage will be covered. Analysis will involve learning new query languages, processing streaming data, and training machine learning models. Most programming will be done in Python.