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Enterprises can access increasing volumes of spatial data (associated with time and space) drawn from a variety of sources including the internet of things, sensors, mobile phone locations and other diverse and unlinked data sets. Managing these data to create useful management insights is a demanding task, and spatial data analysis presents a unique set of challenges and opportunities. Effective management and analysis of spatial data provides strategic value for organisations, across logistics, transport, marketing and other business functions, allowing enterprises to manage strategic challenges in sustainability and resilience. This unit uses real-world data and problem-based learning to develop hands-on experience with managing, processing and modelling spatial data and ultimately drawing insights for business decisions linked to both distribution and supply chain interactions. Students develop highly marketable skills in spatial data analytics that are transferable across a broad range of industries and sectors. These skills include the ability to generate a range of outputs, including decision support systems, maps and visualisations that effectively communicate complex information to support strategic, tactical and operational decision making. This unit utilises a widely-used spatial software package and introduces Geographic Information Systems (GIS), spatial databases and structured query language (SQL).
Code | ITLS6111 |
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Academic unit | Transport and Logistics Studies |
Credit points | 6 |
Prerequisites:
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None |
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Corequisites:
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None |
Prohibitions:
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ITLS6107 or TPTM6180 |
Assumed knowledge:
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Basic knowledge of Excel is assumed |
At the completion of this unit, you should be able to:
Unit outlines will be available 1 week before the first day of teaching for the relevant session.
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