EITT Training Pathways
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Data Analyst (Data Analyst): Contemporary Challenges and Key Competencies (Outlook 2025+)
In the information age, the role of the data analyst is becoming increasingly critical. The main challenges are the explosion in the volume of data (Big Data) and the need to efficiently process, interpret and transform it into valuable business insights. The growing importance of artificial intelligence and machine learning in data analysis further raises the bar, requiring analysts to understand these technologies. The ability to not only technically process data, but also to visualize it and convincingly “tell a story with data” (data storytelling) in order to communicate conclusions to stakeholders, often non-technical ones, is becoming crucial.
Necessary technical skills include proficiency in SQL, programming languages such as Python or R, support for business intelligence tools (e.g. Power BI, Tableau), knowledge of cloud platforms (AWS, Azure, GCP) and ETL tools. Equally important are analytical competencies: critical thinking, problem-solving skills and a solid foundation in statistics. In the area of soft skills, communication skills, curiosity, attention to detail, and an understanding of ethics and data privacy, including regulations such as RODO/GDPR, come to the fore.
The role of the data analyst is evolving from someone who merely processes numbers to a strategic business partner who translates data into action and value. “AI and big data” are at the top of the list of most desirable skills according to WEF , highlighting the strategic importance of the role.
Develop competencies with EITT:
MS PowerBI Desktop
Learn to use BI tools
Tableau basics
Discover the potential of ChatGPT in creating modern applications.
The art of convincing with data: Effective data storytelling
Training in effective communication of analysis results.
Proposed EITT Development Paths
Data Analysis and Engineering Expert (Native Track)
Path Objective:
Achieve mastery of advanced data analysis tools and techniques, data modeling, ETL processes and Big Data technologies.
Recommended EITT Training:
Fundamentals of Analytics and Data Science:
- BIG DATA – data science (Basic Level)
- Introduction to data analysis with R language
- Introduction to Python for data analysts
Business Intelligence Tools:
Databases and SQL
- SQL training
- MonetDB – analytical database
Big Data and Cloud Technologies:
Machine Learning Basics:
Justification:
In-depth knowledge of tools, data analysis techniques and supporting technologies is the foundation of an effective data analyst and engineer.
Data-driven Business Analyst-Strategist (Interdisciplinary Track)
Path Objective:
The development of an analyst who not only processes data, but is able to interpret it in a broad business context, make strategic recommendations based on it, and effectively communicate them to key decision makers in the organization.
Recommended EITT Training (Combinations):
- Selected modules of indigenous analytical skills (as in Track 1)
- The art of convincing with data: Effective data storytelling
- From analyst to strategist – how to use data to create strategic plans
- Effective communication between business and IT
- Business analysis basics (optional) or requirements analysis training from the Management category
- AI Act regulations in business practice (optional) for understanding the legal and ethical framework for using AI
Rationale for Unobvious Connections:
Combining advanced analytical skills with competencies in strategic thinking, effective communication, and an understanding of the business and regulatory context allows the data analyst to become a key partner to the business, actively influencing strategic decision-making. Understanding regulations (e.g., AI Act, RODO) is essential when working with data and AI models, ensuring compliance and ethical conduct.
Optional EITT Supplemental Modules for the Data Analyst
Specialized analytical tools:
Advanced Machine Learning Techniques:
Security and data protection:
Summary Table of Development Paths for Data Analyst.
Ekspert Analizy i Inżynierii Danych (Ścieżka Rdzenna)
MS PowerBI Desktop
Databricks – ujednolicona analityka danych
Analityk – Strateg Biznesowy oparty na Danych (Ścieżka Interdyscyplinarna)
Sztuka przekonywania danymi: Efektywny data storytelling
Od analityka do stratega
Efektywna komunikacja biznesu z IT