Data analysts have become increasingly important during the digital age. Work with data analysis and take on a key role in industries ranging from finance to marketing.
Skilled data analysts are some of the most sought-after professionals in today's labour market. Data analysts have a dynamic skill set, as they are both good at working with numbers and data programs, as well as having strong visual and oral presentation skills. Many industries today have a very high demand for this kind of expertise, and data analysts have a presence in everything from finance, to medicine, to marketing and social media.
A data analyst collects, organizes, and interprets data to give actionable insights for the company or organization they work for. The purpose of data analysis is to answer specific questions that present valuable information for the organization. Working as a data analyst, you will conduct various types of analysis, ranging from descriptive and diagnostic analysis, which tells us what has happened and why, to predictive and prescriptive analysis, telling us what will happen in the future and what actions the company or organization should take.
As data analysts, we are the link between the data and the business, and their ability to make data-driven strategic decisions.Malin Eriksen Birkelund, Atea Analytics
Data analysts have a quintessential portfolio in every modern company ecology. Their ability to guide business leaders to making informed decisions using relevant and up to date information, based on real world data, make them a highly desired addition to every managerial team. Effective data analysis can isolate workflow bottlenecks, reduce operational costs, solve overarching problems, and identify inefficient processes.
The programme incorporates theoretical knowledge, practical skills, and technical competency, to create a balanced learning experience crucial for the development of the data analyst aptitude. You will acquire first hand training in fundamental data identification skills along with accompanying theory.
Data Visualization is a hot topic right now, and deals with being able to convert raw data to easily understandable graphics, to communicate this to boards and CEOs who may not have the technical expertise to understand raw data and numbers.
The programme 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.
Data analysis techniques will be practiced using proxy data sets which will immediately engage your ability to address business oriented problem areas such as operational management, sales, finances, marketing, and even human resources. Finally, the course will cover bleeding-edge data storage, analytic and visualization tools. You will be introduced to online cloud based databases, to enrich your practical skills with industry-desired qualities.
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
After graduation the candidates possess the following learning outcomes (first year):
- has knowledge of data collection, cleaning, organization, and storage of data used in a spreadsheet environment
- has knowledge of the processes and tools that are used for data analysis
- has insight into regulations, the data analysis lifecycle and quantitative versus qualitative data
- has knowledge of processes and tools that are used for data visualization
- has knowledge of problem identification methodologies, processes and tools that are used for problem solving and data error discovery
- has knowledge of conclusive report writing methodologies that are used to communicate results clearly and concisely
- has knowledge of the data analysis field and is familiar with real-world situations to guide decision-making
- can update his/her own knowledge related to the field of data analysis
- understands the importance of data analysis discipline in a societal and value-creation perspective
- can apply knowledge of data model results to business problems
- can apply knowledge of data collection and cleaning from various sources to secure storage and optimize maintenance-masters tools
- masters relevant tools, techniques and material used in data analysis and presentation of results
- can masters tools and techniques to generate and visualise data through reports and info-graphs
- can find information about data analysis techniques and methodologies that are relevant for projects
- can apply knowledge of suitable data analysis use-cases to problems within a current project
- can study workplace environments and identify issues through data analysis and what measures needs to be implemented based on results
- can study a project brief and identify workflow issues and what measures are needed to deliver insight into a project
- understands the ethical principles that apply to sourced, stored, and used data
- has developed an ethical attitude as a responsible data analyst
- can carry out design processes, data models, and applicable techniques based on a project specification
- can build relations with his/her peers and external data specialists and business intelligence agents
- can develop products of relevance to data analysis and optimize his / her own work methods
We recommend the following:
500 GB Hard drive (or 250 GB + cloud storage: fx. Dropbox, OneDrive, Google Drive (recommended).
8 GB RAM.
Microsoft Excel (desktop version)
Core i5 processor.
Both PC and Mac are applicable.
Data analytics offers a wide variety of opportunities across industries and corporate levels. They are vital assets to any company, whether it be large international companies with big data, or fledgling small businesses with monthly sale figures that need to be organized and modelled. Many candidates combine data analysis with other fields of interest that makes use of data. This opens doors to fields such as information science, financial advisory, operational management, medicine, criminal justice, computer engineering, and marketing, to name a few.