IT for Business Data Analytics

On successful completion of the programme, students should be able to: Analyse big data. Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data. Apply statistical analysis techniques. Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyze data, uncover correlations and forecast trends. Handle data samples. Collect and select a set of data from a population by a statistical or other defined procedure. Manage data. Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardization, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialized ICT tools to fulfill the data quality criteria. Normalise data. Reduce data to their accurate core form (normal forms) in order to achieve such results as minimization of dependency, elimination of redundancy, increase of consistency. Report analysis results. Produce research documents or give presentations to report the results of a conducted research and analysis project, indicating the analysis procedures and methods which led to the results, as well as potential interpretations of the results. "At IBS the lecturer doesn't just talk about a topic and gives a lecture, classes are very interactive, which means that you really need to participate."

Programme-specific requirements recorded in SIT Connect.

• A relevant bachelor’s (honours) degree. Applicants are assessed on academic background relevant to the programme
• entry typically expects a 2:2/2:1 (UK) or equivalent.

Proof of English proficiency — typically IELTS, TOEFL, PTE, Duolingo or equivalent (see the minimum scores listed). A Medium-of-Instruction (MOI) letter may be accepted in place of a test by some institutions.

Programme-specific document list.