Data Analyst
(2-year Higher Professional Degree)

Become a highly employable data analyst with advanced skills in databases, cloud services, programmatic data analysis, big data and other advanced topics.

Become a valuable data analyst

As a data analyst, you will have a key role in every modern company’s ecosystem. Your ability to guide organisations to make informed decisions using relevant and up-to-date information based on real-world data makes you a highly desired addition to any team. Effective data analysis can isolate workflow issues, reduce operational costs, identify inefficient processes and contribute to solving critical challenges.

The first year of this two year study program is identical to the Data Analyst one year program. You can still apply directly into this two year program, and secure your place for the full two years.

The second year moves into more advanced areas of data analysis, with courses like Databases and Cloud Services, Programmatic Data Analysis, Critical Data Thinking, Big Data and Advanced Topics, and Interactive Dashboards. This two-year program will make you even more employable to modern and forward-thinking companies.

The programme is aimed at people interested in real-world data and how cold hard numbers and heuristics can be used to shape decision-making using data from other fields of knowledge. This will enable analysts to learn how to leverage results better, visualise information for non-analyst consumption, and report findings elegantly and effectively.

Data Analyst Noroff

Programme objectives

The first year of the program focuses on strong theoretical understanding of analytical models accompanied by practical implementations using industry standard tools, such as Microsoft Excel, Google Spreadsheets, and related technologies. Once the foundation is laid, you will be engaged with how data is collected, stored, organized, analyzed, interpreted, visualized and reported.

This second year expands the technical competency to incorporate more data analytical tools, large data collections and processes for connecting to and querying local or remote databases. You will learn how to solve data problems using industry-relevant statistical tools programmatically.

Advanced data concepts are introduced throughout the second year, allowing you to construct real-world solutions to a broad area of problems. Industry requirements have outlined the need to expand your understanding of business intelligence concepts, data sustainability, and GDPR legal compliance.

Courses in Data Analyst, first year:

  • Data Analysis Fundamentals
  • Data Driven Decision-Making
  • Spreadsheet Fundamentals
  • Statistical Tools
  • Semester Project
  • Evaluation of Outcomes
  • Data Visualization
  • Analysis Reporting
  • Exam Project

Courses in Data Analyst, second year:

  • Databases and Cloud Services
  • Programming Fundamentals
  • Programmatic Data Analysis
  • Semester Project
  • Industry Tools
  • Critical Data Thinking
  • Big Data and Advanced Topics
  • Interactive Dashboards
  • Exam Project

Learning outcomes for the first year can be found on this page. Here follow the learning outcomes for the second year:

The Candidate...

  • has knowledge of concepts and theories that are used in the field of data analysis
  • has knowledge of databases, cloud services and native cloud tools that are used in the field of data analysis
  • has knowledge of programming and programmatic data analysis
  • has knowledge of industry-relevant mutually exclusive tools that are used in the field data analysis
  • has knowledge of essential concepts and theories that are used in data science and engineering in relation to Big Data and data analysis
  • has knowledge of dashboard theory, universal design principles and interactive dashboard development
  • can assess own work within data analysis in relation to relevant regulations and guidelines for GDPR, data maintenance and critical data thinking
  • is familiar with the history, traditions, distinctive nature and place in society of the data analysis discipline
  • has insight into own opportunities for development in the field of data analysis
  • can explain vocational choices in the field of data analysis
  • can explain vocational choices of tools, methods and techniques for data analysis
  • can reflect over own vocational practice into the field of data analysis and adjust it under supervision
  • can reflect on own choices of relevant data analysis tools and work methods and adjust under supervision
  • can find and refer to information and vocational material and assess its relevance to data analysis
  • can find and interact with data from large data sources such as on-premises databases and cloud-based systems
  • can find applicable data models for data sets during a project planning phase
  • can plan and carry out data analysis tasks and projects alone or as part of a group and in accordance with ethical requirements of data maintenance and GDPR principles and practices
  • can exchange points of view with others with a background in the data analysis discipline and participate in discussions about the development of good practice
  • can contribute to organisational quality assurance, streamlining and optimisation through data analysis practices
  • can contribute to solving practical problems relating to the data lifecycle through computational thinking techniques
  • can contribute to data safety by considering security measures during each phase of any data analysis project

We recommend the following specifications for a Windows-based machine, but M1 or M2 MacOS-based devices would also be suitable:
500 GB Hard drive (or 250 GB + cloud storage, e.g. Dropbox, OneDrive, Google Drive (recommended).
16 GB RAM.
Core i7 processor.

Job opportunities

You will be able to work in both national and international companies in need of data analysts. Data analysts have a crucial role in every modern company's ecosystem. After graduation, you are qualified for employment as: Financial analysis, Marketing analysis, Logistics analysis, General data analysis, and Technical analysis.

Get Study Guidance

Do you have questions about the program or your education choice in general? Register and get free study guidance.

Watch recording of livestream

We recommend watching the latest livestream on Data Analyst, hosted by Bertram Haskins and Jessie Rudd 15 March 2023. This is mostly focused on year one.


Programme information


January 9, 2024
March 12, 2024
August 13, 2024
October 15, 2024
Read more about semester start.

Application deadline: Ongoing admissions
Duration: 2 year full time*
4 years part time
Programme language: English
Tuition online:

EUR 4.200,- per semester full time
EUR 2.100,- per semester part time

Accreditations: Approved for loans and grants from the State Educational Loan Fund. NOKUT accredited.
Admission requirements: Admission by formal competence or admission by prior learning. Read more.
Degree: Higher Professional Degree
Credits: 120 ECVET

* A student who has completed Data Analyst one year program can apply directly into the second year.

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