Big Data storage

Designing Data-Intensive Applications, Martin Kleppmann, Chris Riccomini (2026), 2nd Ed., O'Reilly Media Moniruzzaman, A.B., Hossain, S.A. (2013). NoSQL Database: New Era of Databases for Big data Analytics - Classification, Characteristics and Comparison. Maribel Yasmin Santos, Carlos Costa (2019). Big Data, FCA.
Data Science
6321
23089
Big Data storage
ISMAT6321-23089
2
6
0
12
Não
Português
The teaching methodology includes the expository method (TM1) to present the contents, the demonstrative method (TM2) to illustrate its application to practical cases and the active method (TM3) to solve classroom exercises, with the use of a computer. The assessment is made by continuous assessment or written exam. The continuous assessment consists of two written tests with a weight of 30% each and a group work (40%).
Mandatory
LO1: Know the technologies for storing large volumes of data; LO2: Develop and maintain repositories supported by distributed information systems, to handle large volumes of data; LO3: Design databases and extract data in MongoDB; LO4: Manipulate JSON structures.
S1: Introduction to Non Relational Databases; S2: Redundancy as a tool to manage fault tolerance; S3: Distribution of data to manage large volumes of data; S4: Introduction to MongoDB; S5: Database Design in MongoDB; S6: Manipulation of JSON structures; S7. Extraction of data in MongoDB.

As componentes de avaliação são as seguintes:

Semestral
The Big Data Storage course aims primarily to introduce students to the technologies, models, and practices used for storing and managing large volumes of data. In a context where the volume of generated information is constantly growing, it is essential to understand solutions that ensure scalability, fault tolerance, data distribution, and efficient access to information. This course focuses specifically on non-relational databases, distributed systems, and technologies such as MongoDB, enabling students to acquire practical skills in the design, maintenance, and utilization of data repositories tailored for Big Data scenarios.