Level 7

Take the next step in your data science and information technology (IT) career

Learn what it takes to make sense of data and how to use it to drive innovative solutions to real-world problems from forecasting the effects of climate change to predicting health outcomes for hospital patients.

Programme highlights

Get the training to use your analytical and problem-solving skills to leverage the true value of data for organisations all over the world.

You will be well equipped for a career in this exciting and constantly changing field as you learn to design, develop and use front and back-end data manipulation, security and data warehousing processes and technologies to support decision making and solve business problems.

As well as a strong grounding in analytical, technical and theoretical concepts this degree also uses hands-on practical methods and teaches important people skills like communication and management skills.

As the culmination of this programme, you’ll be able to do a real-world project where you can apply your skills in the workplace.

Download the programme guide

Entry requirements

Entry requirements

Applicants must meet the following criteria for admission into the programme:
  • Successfully completed a bachelor’s degree in any field excluding the specific graduate diploma field; or
  • Successfully completed a Level 6 or 7 Diploma and relevant work and/or life experience (equivalent to a Bachelor’s degree); or
  • Evidence of equivalent practical, professional or educational experience e.g. three-five years’ full-time work experience (relevant to ICT studies).
English language entry requirements

Applicants must have sufficient competence in the English language to undertake this programme which is taught and assessed in English. This will be demonstrated by meeting the current NZQA requirements.

For the minimum English language requirements refer to: manukau.ac.nz/english-req

Provisional entry

Students who have attained the age of 20 years and do not hold the minimum entry requirements for a programme or training scheme may be eligible to be enrolled. Such decisions must consider any applicable pre-requisites and will be made by the Head of School. Students who have not attained the age of 20 years and do not hold the required minimum entry requirements may also be eligible to be enrolled in exceptional circumstances where they can demonstrate capability for study at the required level. Such decisions must consider any applicable pre-requisites and will be made by the Head of School.


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Programme structure

Programme structure

You will need to complete the below seven courses (120 credits):

Level 6

563.684 Big data analysis (15 credits)

This course is designed to understand essential attributes, contemporary issues, opportunities, risks and challenges of big data; to explain the concepts and techniques of data integration, cleansing, processing and analysing; to design and implement a data warehouse; to understand the modelling requirement, approaches and complexities of data mining; and to create decision models and produce reports and business intelligence to support complex decision scenarios.
Prerequisite: 564.532 Introduction to Databases;502.524 Fundamentals of Business Intelligence.

563.685 Business statistics for decision modelling (15 credits)

The purpose of this course is to understand, construct and apply statistical models to assist business decision-making and problem-solving; and to demonstrate an understanding of forecasting strategies, detecting trends and making predictions from regression analysis and simulation of time series data;

563.686 Data analytics and intelligence (15 credits)

The purpose of this course is to explain how businesses can use big data analytics to drive business growth and discover how data analytics will change the way organisations make products, market services and engage with customers; and to analyse big data sets using visualisation techniques to create decision scenarios.
Prerequisite: 502.524 Fundamentals of Business Intelligence.

Level 7

563.783 Management of ICT (15 credits)

The purpose of this course is to learn and apply appropriate frameworks, architectures, tools and techniques for analysing business and ICT infrastructure to prepare ICT strategies, policies, protocols and action plans; to align business processes with information systems processes; to prepare an ICT risk management plan, and to understand the influence of ICT innovations in organisational management;
Prerequisite: 561.590 Business Information Systems; and 563.683 Change and Project Management in IT.

563.784 Advanced data analytics (15 credits)

This course focuses on designing, developing and implementing an advanced business intelligence system from a big data set using a data analytic tool. The students learn how to translate a business problem into the design of a data analysis strategy; to develop an advanced business intelligence solution that performs data manipulations using a variety of models in a selected big data analytic environment, and to critically examine and interpret the model outputs and test the performance of models;
Prerequisite: 563.686 Data Analytics and Intelligence

563.785 Hot topic in data analytics (15 credits)

The purpose of this course is to apply the concepts, techniques, tools and models of big data and data analytics to create a useful solution for a given business problem in a selected industry.

563.786 GDICT industry project (30 credits)

The opportunity to design, implement and evaluate a project for a client by integrating the theory learnt in underpinning courses and applying this practically in an industry environment.
Prerequisite: Level 7 courses in selected major.

Careers and pathways

Career opportunities

Opportunities for employment include:

  • IT manager, web developer
  • Programmer
  • Software developer
  • Software architect
  • Systems analyst
  • Business analyst
  • Network/software support specialist
  • Multimedia developer
  • User experience designer
  • Network/database administrator
  • Business and data analytics professional
  • IT project manager (incorporating business analytics and intelligence).

For potential salaries visit careers.govt.nz.

Recognition of Prior Learning (RPL)

Your work experience or previous tertiary study may count towards achieving your qualification. Recognition of Prior Learning (RPL) at MIT is designed for those who already have on-the-job skills and knowledge, but want to take their career to the next level with a qualification.

With RPL we can measure and match your existing skills against credits in our courses – creating a tailored path of study that will not only save you money but also help you to complete your qualification faster. Learn more.

Information is correct as at 4 November 2022. Programme fees are based on a full-time student and may vary depending on your final selection of courses that make up your programme. To provide you with an indication of costs, the approximate fees quoted in this publication are based on the indicative 2023 fee structure. The indicative programme fees for 2023 do not include the Compulsory Student Services Fee (CSSF). The CSSF is an additional levy to your 2023 programme or course fees. Further information about the CSSF can be found here www.manukau.ac.nz/cssf. Programmes stated as eligible for free study in 2023 are based on the 2022 fee structure and subject to funding confirmation for 2023. All fees are in New Zealand Dollars. You will be advised of the current fees at the time of enrolment. All courses and programmes will proceed subject to numbers and academic approval. Manukau Institute of Technology is part of Te Pūkenga – New Zealand Institute of Skills and Technology. Te Pukenga is accredited under the provisions of the Education and Training Act 2020. International students must study in class and will not be able to enrol for online study options.