JST495 Intelligence and analytics (8)


This subject provides the student with an advanced understanding and mastery of data mining and analytics in the national security, policing and business intelligence contexts.   Students will develop a deep understanding of data, and how to interpret patterns  in it using various analytical methodologies.  Students will also be introduced to and apply a range of prediction technologies and competitive analytical techniques increasingly being used by intelligence officers and investigators.  Students will apply these skills to a range of examples including but not limited to: fraud, counter-terrorism, money laundering and other financial crimes. The subject takes a multi-disciplinary approach so that students from different intelligence contexts (national security, policing and business) can learn from other practice areas.  Whilst the subject is focused on developing data mining and analytics skills in the intelligence practitioner,  investigators and managers who seek to build these skills in their agencies will also benefit from this subject.

+ Subject Availability Modes and Location

Session 1
DistanceManly Campus
Session 2
DistanceManly Campus
Continuing students should consult the SAL for current offering details: JST495
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One sessionHD/FLAustralian Graduate School of Policing and Security

Assumed Knowledge

It would be beneficial for the student to have some knowledge of basic intelligence theory and practice. Though this is not mandatory or required for successful completion of the subject.

Learning Outcomes

Upon successful completion of this subject, students should:
  • Mastery and understanding of contemporary theoretical knowledge and discourse on data mining, analytics and knowledge discovery techniques in the intelligence context.
  • Use a range of analytics tools in supporting tactical/operational analysis and demonstrate being able to apply appropriate techniques to different analytical problems.
  • Collect, analyse, consolidate and synthesise operationally relevant information and provide reports (intelligence reports) that can describe and explain a range of security threats and provide solutions and reccommendations to address these.
  • Demonstrate an understanding of the intelligence and analytical concepts for intelligence practice


The subject will cover the following topics:
  • Topic 1 Introduction
  • 1.1 What is data mining and analytics?
  • 1.2  Intelligence and the applications of data mining and analytics
  • Topic 2 Data
  • 2.1 Kinds of data
  • 2.2 How is data collected?
  • 2.3 Fusion of different kinds of data
  • 2.4 Problems with data
  • Topic 3 Knowledge Discovery
  • 3.1 Introduction to knowledge discovery
  • 3.2 Sense making
  • 3.3 Looking for risk/predictive analysis
  • Topic 4 Applying intelligence and analytics to real world problems
  • 4.1 Practical exercises
  • 4.2 Business intelligence
  • 4.3 Competitive analytics
  • Topic 5 Contempoary issues and problems


The information contained in the 2016 CSU Handbook was accurate at the date of publication: 06 September 2016. The University reserves the right to vary the information at any time without notice.