The teaching of the "Database Technologies" discipline is relevant as the modern era of information technology is characterized not only by the growth in data volumes but also by a fundamental shift in its nature and structure. Classical relational systems are no longer sufficient for effectively managing the heterogeneous, semi-structured, and highly connected data generated by web applications, social networks, and Internet of Things devices. Today's IT specialists face the need to choose the right tool for each specific task, making an understanding of the diverse world of NoSQL solutions a key competency.
Even a minimal awareness in this field allows for the development of significantly more productive, scalable, and flexible software systems. An understanding of the principles behind document, in-memory, and graph databases enables the creation of architectures that optimally meet business requirements and effectively leverage cloud technologies, microservices, and big data analytics systems.
Modern database technologies represent an ecosystem of diverse storage solutions, where traditional SQL systems coexist with non-relational (NoSQL) ones. The main advantage of this approach, known as "Polyglot Persistence," lies in the ability to select a specialized tool for each type of data and workload, ensuring maximum efficiency, development speed, and scalability.
The academic discipline "Database Technologies" is designed for higher education students pursuing a bachelor's qualification level.
The study of this discipline involves developing a full range of skills for working with key categories of modern NoSQL databases. Students will become familiar with the document-oriented DBMS MongoDB, mastering its query language for CRUD operations and data analysis; understand the operational principles of the in-memory store Redis for implementing caching; and grasp the graph data model through Neo4j and its declarative query language, Cypher.
The aim of the "Database Technologies" discipline is for students to acquire theoretical knowledge of key NoSQL data models and confident practical skills for selecting, deploying, and effectively utilizing non-relational databases in modern software projects.
The objectives of the academic discipline are the sequential mastery by students of the concepts, models, and technologies of modern non-relational databases. This includes:
∙ Understanding the limitations of the relational model and the reasons for the emergence of the NoSQL movement.
∙ Applying practical CRUD operations and the Aggregation Framework in the document-oriented database MongoDB.
∙ Developing skills in implementing the caching pattern using the in-memory store Redis.
∙ Mastering the fundamentals of graph thinking and the Cypher query language for working with highly connected data in Neo4j.
∙ Developing the ability to analyze system requirements and select the optimal database type for each specific task.
The subject of the academic discipline is the models, methods, and tools for designing, creating, organizing, and manipulating data in non-relational (NoSQL) databases.
The object of the academic discipline is the architecture of modern information systems and their data storage components, their principles of operation, and methods of management, demonstrated through the DBMS examples of MongoDB, Redis, and Neo4j.
The learning outcomes and competencies formed by the course are defined in table 1
Table 1
Learning outcomes and competencies formed by the course
|
Learning outcomes |
Competencies |
|
LO 1 |
SC 1 |
|
LO 2 |
SC 2 |
|
LO 3 |
SC 4 |
|
LO 4 |
SC 5 |
where LO 1 – to apply knowledge of the state language and foreign languages for the purpose of ensuring effective professional communication;
LO 2 – to organize one's own professional activity, select optimal methods and means for solving complex specialized tasks and practical problems in professional activity, and to assess their effectiveness;
LO 3 – to use the results of independent search, analysis, and synthesis of information from various sources for the effective solution of specialized professional tasks;
LO 4 – to analyze, provide arguments, and make decisions when solving complex specialized tasks and practical problems in professional activities, characterized by complexity and uncertainty, and to be responsible for the decisions made;
SC 1 – ability to apply knowledge in practical situations;
SC 2 – knowledge and understanding of the subject area and an understanding of the profession;
SC 4 – ability to identify, formulate, and solve problems within the professional field;
SC 5 – ability to search for, process, and analyze information.- Лектор: Венгріна Олена Сергіївна