Big Data Analytics

Educational Process

The Big Data Analytics program at the EIU in Poland equips students with the necessary skills to exploit big data tools and methods. Pursuing a degree in Big Data Analytics at the European School of IT gives students the ability to learn how to collect, manage and analyze big, fast-moving data for science or commerce. Participants of academic mobility programs and international students at the IEU in Poland gain skills in cutting-edge technology such as Data Analytics, R, Hadoop, NoSQL, and Machine Learning. The course gives insight into essential maths and computing theory and teaches international students to use advanced computational techniques.

The Big Data Analytics Degree program at the European School of IT is taught using a combination of lectures, seminars, group work, presentations, and laboratories with coursework and exams used for assessment. The IEU, Poland students undertake individual research projects under the supervision of a faculty member. Practical classes are conducted in fully equipped computer labs with the latest software and technologies. The computers have industry-like capabilities to run complex analytical computations through software like Tableau, SAS, IBM Watson, Python, and Matlab. The curriculum is taught by expert faculty with real-world experience ensuring students gain the competencies needed in the field of Big Data Analytics. The staff of professionals at the European School of IT is ready to support international and foreign exchange students’ needs providing a collaborative learning environment with quality interaction between faculty and students.

IEU, Poland has its digital educational platform, which combines European Studying Curriculums and modern technical equipment. It helps IEU, Poland students quickly and easily learn new information required in their work process. University-renowned classrooms and reading rooms, IEU, Poland Library with thousands of books and scientific journals, and Digital IEU, Poland Library with access to electronic resources are freely accessible to students and staff at any time they need it. The Big Data Analytics degree at the IEU in Poland allows exchange and study abroad students to join internship programs, study abroad programs in Europe, and interactive online courses.

After graduating students are able:

• Gather and accumulate data from disparate sources, clean it, organize it, process it, and analyze it;
• Identify new sources of data and develop methods to improve data mining, analysis, and reporting;
• Write SQL queries to extract data from the data warehouse;
• Create data definitions for new database files or alterations made to the already existing ones for analysis purposes;
• Present the findings in reports (in table, chart, or graph format) to help the management team in the decision-making process;
• Monitor the performance of data mining systems and fix issues;
• Manage master data, including creation, updates, and deletion;
• Provide quality assurance of imported data, working with quality assurance analysts if necessary;
• Organize commissioning and decommissioning of data sets;
• Apply statistical analysis methods for consumer data research and analysis purposes;
• Keep track of the trends and correlational patterns among complex data sets;
• Perform routine analysis tasks to support day-to-day business functioning and decision-making;
• Collaborate with Data Scientists to develop innovative analytical tools;
• Work in close collaboration with both the IT team and the business management team to accomplish company goals;
• Design and maintain data systems and databases;
• Fix coding errors and other data-related problems;
• Reorganize data in a format to be easily read by either humans or machines;
• Interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts;
• Creating appropriate documentation allows stakeholders to understand the steps of the data analysis process and duplicate or replicate the analysis if necessary;
• Support the data warehouse;
• Support initiatives for data integrity and normalization;
• Implement new or upgraded software and assist with strategic decisions on new systems;
• Evaluate changes and updates to source production systems;
• Train end-users on new reports and dashboards;
• Provide technical expertise in data storage structures, data mining, and data cleansing;
• Select and integrate any Big Data tools and frameworks required to provide requested capabilities;
• Implement ETL process;
• Define data retention policies;
• Identify, analyze, and interpret trends or patterns in complex data sets;
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems;
• Work with management to prioritize business and information needs.