Information Systems and Big Data

Course title: Information Systems and Big Data

Code: 3ФЕИТ07Л009

Number of credits (ECTS): 6

Weekly number of classes: 2+2+1+0

Prerequisite for enrollment of the subject: None

Course Goals (acquired competencies): Working with distributed databases. Fragmentation of databases. Working with large data. Upon completion, the student will be able to create data fragments and create, analyze and handle large data.

Total available number of classes: 180

Course Syllabus: Introduction to large databases. Distribution of data. Concepts, advantages and disadvantages of distributed data. Creating Distribution. Distribution of data by dividing by selection (horizontally). Distribution of data by means of projection split (vertically). Access and processing of issues in data distribution. Designing DB according to data distribution. Adjustment of DB according to requirements. Ways to optimize DB according to the queries. Optimizing by location. Introduction to Data Warehouses. Defining and Concept of Warehouses.  Work with OLAP and OLTP. Types of data warehouses. Modeling warehouses. Star and snowflake pattern. Object Database. Pure-object databases. Object model. Object-relational databases. SQL mapping in ORBP. Data mining of large data. Algorithms of machine learning and AI. Large data analysis. Related large data structures. Analysis by graphs.

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