• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
Bachelor 2020/2021

Data Management

Area of studies: Business Informatics
When: 2 year, 3, 4 module
Mode of studies: offline
Open to: students of one campus
Language: English
ECTS credits: 5

Course Syllabus


As the amount of data being produced everyday increases, the skill of working with data sources (databases) becomes an essential one for anyone involved in IT or management. After completing the Data Management course students will be able to create a normalized relational database, connect to an existing data source, write complex SQL queries to read and modify the data and prepare business intelligence reports. The course mostly focuses on relational data models, database design and data manipulations with use of programming language. Non-relational databases, physical storage organization and access management are additional topics of the course. The course introduces students to the popular and widely used database server - PostgreSQL.
Learning Objectives

Learning Objectives

  • Provide students with necessary knowledge and practical skills in business database design and maintenance
  • Learn to use SQL programming language to read and process the data stored in a relational database
Expected Learning Outcomes

Expected Learning Outcomes

  • Identify data model types
  • Organize data in table form
  • Use spreadsheet tools to store and process data
  • Use client software to manage and fill a relational database
  • Find a plan for retrieving data from a relational DB in terms of relational operations
  • Describe a relational database schema
  • Explore dependencies of attributes and solve data redundancy problems
  • Use query editor to write and execute queries
  • Retrieve data from connected tables
  • Use calculations in SQL queries
  • Write analytical queries with aggregation
  • Develop complex queries with use of window functions
  • Create database objects with SQL - procedures, functions and views
  • Track and process changes in table data with triggers
  • Identify entities and relationships based on business rules analysis and create conceptual and logical models
  • Build a logical data model on top of a conceptual model
  • Use IDEF1X method to create a database
  • Prepare reports and dashboards to provide access for users to business-critical information
Course Contents

Course Contents

  • Introduction to data management. Database systems
    Main data models. DBMS vs database. Features of DBMS. Benefits of RDBMS. Data structure. Key concepts of DBMS. Client tools for managing a database. Spreadsheet applications. Useful data formats.
  • Relational data model and relational algebra
    Relations. Keys. Schema of relational database. Relational algebra operations. Main and additional operators. Normalization algorithm. Five normal forms. Functional dependencies. Multivalued dependencies.
  • Database design
    Database design techniques. Subject area analysis. Entityes and relationships. Conceptual models. Logical models. IDEF1X. Subtypes and supertypes. Using CASE tools to create a database from scratch.
  • Data manipulations in structured query language. Create, read, update and delete operations.
    General information on writing queries. Structure of SELECT statement. Type-specific manipulations. Expressions. Connecting records of tables in SELECT. Modifying table data with SQL queries.
  • Advanced SQL. Analytical queries. Procedural SQL
    Aggregate functions and grouping. Writing analytical queries with expressions, derived tables and filters. Complex queries. Three types of window functions. Views, procedures, functions. Triggers. Passing parameters to procedures and functions.
  • Reporting and data visualization
    Maintaining data views for users by means of reports. Dashboards and BI-systems. Setting navigation between different reports.
Assessment Elements

Assessment Elements

  • non-blocking Team project
  • non-blocking Test
  • non-blocking Exam
  • non-blocking Practice
  • non-blocking Quiz on lecture
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.2 * Exam + 0.25 * Practice + 0.1 * Quiz on lecture + 0.25 * Team project + 0.2 * Test


Recommended Core Bibliography

  • Garcia-Molina, H., Ullman, J. D., Dawson Books, & Widom, J. (2014). Database Systems: Pearson New International Edition : The Complete Book (Vol. Second edition). Harlow, Essex: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1418178
  • Hoffer, J. A., Ramesh, V., & Topi, H. (2016). Modern Database Management, Global Edition (Vol. Global edition, Twelfth edition). Boston: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1419666

Recommended Additional Bibliography

  • Clark, D. (2017). Beginning Power BI : A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Vol. Second edition). Camp Hill, Pennsylvania: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1478775
  • Foster, E. C., & Godbole, S. (2016). Database Systems : A Pragmatic Approach (Vol. Second edition). [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1174505