Data Management

2025/2026

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Economics

Course type:

Compulsory course

When:

1 year, 4 module

Instructor

Сичинский Антон Евгеньевич

Course Syllabus

Abstract

Managers need to be properly informed in order to make effective business decisions. In modern organizations, data is often distributed across multiple systems, departments, and formats, making it difficult to access, interpret, and use efficiently. Moreover, the lack of proper data management practices leads to low data quality, inconsistent definitions, and limited trust in analytical results. This course introduces students to the principles and practices of data management and demonstrates how data can be transformed into actionable insights using modern self-service tools. The course covers the full data lifecycle — from data collection and preparation to analysis and visualization — with a strong emphasis on practical skills. Students will learn how to work with raw and heterogeneous data, apply data transformation techniques, and build analytical data marts using a low-code approach in Polyanalyst GRID. The course also focuses on data visualization and dashboard design using PIX BI, enabling students to present insights in a clear and business-oriented way. Practice includes data profiling, cleansing, transformation, and exploratory data analysis, followed by building dashboards and interpreting results in a business context.

Learning Objectives

•  - Provide students with a comprehensive understanding of data management principles and frameworks  - Develop practical skills in data preparation and transformation using self-service tools  - Introduce core concepts of data governance, data quality, and data lifecycle  - Enable students to perform exploratory data analysis and generate insights  - Teach principles of effective data visualization and dashboard design  - Prepare students to work with data in real-world business scenarios

Expected Learning Outcomes

• Understand the role and value of data management in organizations
• Explain the difference between data, information, and knowledge (DIKW concept)
• Understand the data lifecycle and key components of data management
• Perform data transformations using low-code tools
• Build analytical datasets (data marts) for business analysis
• Design and create dashboards using BI tools

Course Contents

• 1. Introduction to Data Management and Data Analysis
• 2. Data Management Processes, Lifecycle, and Governance
• 3. Business Intelligence and Data Visualization Principles
• 4. Practical Module: Data Preparation and Visualization
• 5. Final Project (Presentation and Defense)

Assessment Elements

• Quiz 1
• Quiz 2
• Final Project
  Final Project is a team-based project (students work in teams of 4-5 ). The objective is to perform an end-to-end analytical workflow — from raw data to actionable business insights — and to present the results in a final project presentation session.

Interim Assessment

• 2025/2026 4th module
  0.25 * Quiz 2 + 0.5 * Final Project + 0.25 * Quiz 1

Bibliography

Recommended Core Bibliography

• John Ladley. (2020). Data Governance : How to Design, Deploy, and Sustain an Effective Data Governance Program: Vol. Second edition. Academic Press.

Recommended Additional Bibliography

• Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit : The Definitive Guide to Dimensional Modeling (Vol. 3rd edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=605991

Authors

• BRODSKAYA NATALYA NIKOLAEVNA