Data Intelligence in Practice - BUSN7980

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2024 to 2025
Canterbury
Spring Term 6 15 (7.5) Ricky Mak checkmark-circle

Overview

The constant evolution of data intelligence and big data analysis means there has never been a higher demand for great data analysts, the kind you'll become at Kent Business School. You’ll learn how to use data analysis and computer programming techniques to get the crucial information and actions from data to drive results in business. Through your use of Python, you’ll make rapid progress towards mastering data visualisation and analysis skills, so you'll not only understand data, you’ll also be able to make other people understand it as well. Your ability to turn data into clear messaging for stakeholders will make you a key asset to any business.

Details

Contact hours

Private Study: 128
Contact Hours: 22
Total: 150

Method of assessment

Main assessment methods:
In-Course Test 1 (45 minutes) 20%
In-Course Test 2 (45 minutes) 20%
Group Presentation 20%
Individual Report (1500 words) 40%

Reassessment methods:
100% coursework

Indicative reading

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Display conceptual understanding of the usefulness of data in improving business and organisational performance.
- Develop systematic approaches to realising the benefits of data to organisations that align with overarching business strategy;
- Critically analyse the data requirements for improving an area or process of a business.
- Create visualizations and interactive dashboards to gain new insights from data.
- Leverage the power of data-driven storytelling to help messages resonate with a business audience.
- Understand how to employ participatory methods in identifying data requirements, structure complex problems, and ensure stakeholder uptake of data intelligence solutions.


The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Identify and critically analyse complex business problems amenable to a data-driven solution.
- Appreciate the power of data intelligence for decision making and business value creation.
- Work effectively individually and in groups.
- Deliver effective oral presentations to engage a business audience and gain buy-in of the usefulness of analytics solutions for complex managerial problems.

Notes

  1. Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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