Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
• To develop specialist skills and techniques required by industry to deliver value from data analytics.
• To query, manage, analyse and visualise data using industry standard software in order to identify and address potential organisational strengths, weaknesses, threats and opportunities.
• To manage independent learning in order to deepen knowledge and reflection on the topic through a range of learning activities that might include extended reading, reflection, research and practical exercises.
1. The world of data and digital
2. Data types and structures
3. Data cleansing strategies and tools
4. Data manipulation capability via common desktop tools - Excel
5. Logical thinking and logic statements
6. Insights and Visualisation
7. Dashboards as mechanisms for management reporting
8. Developing investigatory capability
9. Developing data driven ‘storytelling’ capability
Topics 6 to 9 would be delivered by industry standard visualisation tools, for example Tableau or Microsoft Power BI.
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 30:00 | 30:00 | N/A |
| Scheduled Learning And Teaching Activities | Lecture | 2 | 1:00 | 2:00 | PIP Lectures |
| Guided Independent Study | Directed research and reading | 1 | 33:00 | 33:00 | N/A |
| Scheduled Learning And Teaching Activities | Small group teaching | 8 | 2:00 | 16:00 | PIP workshops - PC lab based |
| Guided Independent Study | Independent study | 1 | 19:00 | 19:00 | N/A |
| Total | 100:00 |
Guidance provided at the beginning of a session are used to present the underlying theory and practical capability, with emphasis on choosing appropriate methods in relation to business needs and dedicated applications. A workshop environment will then allow you to:
1) Interpret theory through relating the taught material to real world business problems.
2) Formulate a plan for implementing data analytics to enhance business decision making.
3) Develop enhanced capability in practical data analytics.
The format of resits will be determined by the Board of Examiners
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 2 | M | 100 | 2000 words |
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Lab exercise | 2 | M | N/A |
Formative assessment
The module has been designed so that students will work on some of the elements required for their summative assessment during the teaching sessions throughout the semester via a teaching dataset defined as Lab Exercise Students will be invited to discuss their progress in class as a case study. This has a number of benefits:
• Student are producing work that can be adapted for use with their summative assessment
• Students can debate and share good practice
• Students will receive feedforward on these discussions.
Summative Assessment
The final report is designed to allow students to provide a reasoned set of management recommendations based on practical implementation of key principles of data manipulation, insight generation, visualisation and data driven outcomes.
The individual component must be submitted in the assessment period following the taught elements. Each student will be required to produce a 2000 word report.
Feedback Strategy
Formative: as stated earlier, there will be a number of opportunities where formative feedback will be provided throughout the module, particularly in relation to practical tasks.
Summative: For each component of assessment there is a respective standard marking criteria that will indicate how marks are allocated to the work, alongside the annotated comments on the work and overall summary comments provided using electronic marking.