Master of Business Information Systems (Data Analytics)

Master of Business Information Systems (Data Analytics)

Course Overview

The AIH Master of Business Information Systems (Data Analytics) is designed for professionals to gain advanced technical skills and expertise in areas of data science and analytics. As business professionals or ICT specialists, graduates not only understand how to compile datasets but also how to analyse and interpret data to identify the most relevant information. These insights can be incorporated into the organisational business decision-making process to facilitate decision-makers and managers. Graduates will develop the technical, analytical skills and strategic awareness to use data to influence business change.

Nested Qualification and Exit Awards

Key information

CRICOS Code: 111495D

Duration:

2 years full time

AQF level:

9

Campus:

– Sydney
– Melbourne (commencing 2024)

Course Intakes:

February, May, August, October

Student:

Domestic and International

Credit points per unit:

10

Total Credit Points
required for award:

160

2023 Fees

Course tuition Fee
Over 2 years

$44,000

Fee per annum:

$22,000

Fee per unit:

$2,750

Notes:

All fees and charges listed are in Australian dollars. Fees are subject to change without notice. Course fees are to be paid in full before enrolment/selection of subjects in any given semester. AIH ensures that the conditions and processes for international and domestic students to apply for a refund of tuition fees are equitable and comply with government regulations. Refer to Refund Policy for International and Domestic Students.

What you will learn

Admissions and Completion of Study

Students wishing to join the postgraduate courses should review the entry criteria and application procedures which are published in the Institute’s Course Guide.

This Master Course (111495D) is awarded after successfully completing 15 units of study. Students wishing to exit with a Graduate Certificate of Business Information Systems (Data Analytics) (105294H) may do so after the successful completion of 4 units. Students wishing to exit with a Graduate Diploma of Business Information Systems (Data Analytics) (111496C) may do so after the successful completion of 8 units.

Study Hours

This course is offered as a face-to-face course at the Sydney or Melbourne campus. As a student, you will need to allocate time to attend classes. Generally, units will be delivered in a standard form in a 4-week block model comprising 2 sessions of 4 hours each per week. Some special units will be delivered in an intensive form in a 4-week block model, comprising 2 sessions of 6 hours each per week for 3 weeks and a 4th week for assessment submission. In addition, you will need to set aside approximately 7-9 hours per week for each unit in your own time to complete assignments, readings, and projects, and to prepare for workshops or presentations with QA sessions.

Assessment

Your studies at AIH will encompass practical, professionally focused, and project-based learning, so assessment types will vary. You can expect them to include (the list is not exhaustive):

  • Individual and team-based projects
  • Case studies and presentations
  • Essays, assignments, and reports
  • Final assessments, presentations, and QA sessions
  • Practical assessments
  • Discussion forums
  • Participation in class, including formative assessment activities

Learning Outcomes

  1. Integrate advanced concepts and practices of data analytics within the business information systems field.
  2. Contrast data analytics issues within complex business scenarios, and design and propose solutions to demonstrate mastery of professional practice.
  3. Evaluate the effectiveness of complex data analytics systems and strategies within specific industry contexts.
  4. Assess existing data analytics trends in order to apply appropriate tools and techniques to support decision-makers in a professional context.
  5. Formulate well-researched data analytics and business information systems recommendations for relevant stakeholders.
  6. Exhibit leadership, management and interpersonal skills required to effectively work in a diverse team on business information systems and data analytics projects.
  7. Resolve current ethical dilemmas and professional issues in business information systems with a focus on data analytics.

Knowledge

Graduates at this level will have advanced and integrated understanding of a complex body of knowledge in one or more disciplines or areas of practice.

Skills

Graduates at this level will have expert, specialised cognitive and technical skills in a body of knowledge or practice to independently:

  • analyse critically, reflect on and synthesise complex information, problems, concepts and theories
  • research and apply established theories to a body of knowledge or practice
  • interpret and transmit knowledge, skills and ideas to specialist and non-specialist audiences

Application

Graduates at this level will apply knowledge and skills to demonstrate autonomy, expert judgement, adaptability and responsibility as a practitioner or learner.

Units you will study

Structure

Master of Business Information Systems (Data Analytics) will help students to gain advanced technical skills and expertise in areas of data analytics. This course has 15 Units (160 credit points including Capstone Project with 20 credit points). There are 13 units that are compulsory and 2 units that are electives. The units and their descriptions are listed below.

Level 4000 (AQF 8)+

MBIS4001 Information Systems Applications in Business-

Unit Description

MBIS4001 Information Systems Applications in Business provides an introduction to the subject of information systems (IS) by presenting the most relevant concepts used to manage the integration of IS into business and society. The purpose of the unit is to facilitate proficient ways to simplify the use of technology in complex IS business environments and, by using case studies together with examples from industry, students will develop both a theoretical and a practical understanding of business information systems in order to achieve this.

More, this unit aims to build students’ awareness of the relationship between the functionality of IS and the requirements of business processes. In this way, students will learn how business organisations use IS to process data into information which can then be used for critical decision- making in the quest for competitive advantage.

MBIS4002 Database Management System-

Unit Description

Database management systems are ubiquitous. Almost all organisations adopt them to organise, analyse, extract, transform and load data in order to make effective decisions. This positions MBIS4003 Database Management System as an essential unit as it introduces students to the fundamentals of relational databases. Unit learning outcomes are attained through authentic assessment; that is, the application of relevant concepts, techniques and methodologies related to database management along with practical exercises.

This unit also covers data modelling associated with using entity relationship diagrams and other advanced concepts such as structured query language (SQL) and procedural language (PL). These will be completed in the weekly workshops.

Additionally, data analysis, sharing options and database systems security concepts are covered. Distributed database management systems and data mining are also included in the unit’s topics.

MBIS4003 Software Development-

Unit Description

In this unit, MBIS 4003 Software Development, students will learn the fundamentals of software development. Students will investigate a client’s application software problems, evaluate approaches, and then design a solution using a programming language such as Python. The unit takes students through the lifecycle of a software development project including writing specifications, testing and design. Students will gather and analyse customer software needs and requirements, learn core principles of programming, develop software specifications and use appropriate reference tools. Upon successful completion of this unit, students will have the ability to assess, understand and design code.

MBIS4004 Systems Analysis Design-

Unit Description

MBIS4004 Systems Analysis Design covers the principles of analysis and design for information systems. Students will learn techniques in data requirements gathering and analysis along with methods to model data needs. Modelling of data will occur at the conceptual, logical, and physical levels along with an ability to compare and contrast different approaches.

Additionally, students will understand the importance and constraints imposed by the domain of the information system, along with business rules that guide the design of business information systems. This unit also addresses the role of functional dependencies and domain normalisation as part of requirements analysis and design using a user-centred design approach. At the end of this unit, students will have a sound understanding of the techniques required to model an information system.

Exit Point: Graduate Certificate of Business Information Systems

MBIS4007 Big Data and Visualisation-

Unit Description

MBIS4007 Big Data and Data Visualisation introduces students to the concepts that inform big data analytics and visualisation. It will help students gain insights on how big data drives and supports an organisation’s strategy and how data centricity helps to make better business decisions.

The unit provides in-depth coverage of business motivations and drivers for big data adaptation, enterprise technologies and big data business intelligence. Topics covered will also include algorithms and machine learning techniques for big data and data science.

Furthermore, students will develop an understanding of data visualisation tools and techniques that will help them present information and data using appealing and informative dashboards. In summary, this unit aims to provide students with an ability to discover trends and outliers in the data using big data and visualisation principles, concepts, tools and techniques through hands-on practice.

Pre-requisite: MBIS4002 & MBIS4003

MBIS4008 Business Process Modelling-

Unit Description

MBIS4008 Business Process Modelling facilitates students in examining and improving business operations. Informed by conceptual frameworks, students will use business process modelling software tools to make informed recommendations aimed at solving complex business problems as well as attendant improvements to organisational effectiveness and efficiency. This unit provides an opportunity for students to develop the knowledge and skills necessary and sufficient to analyse and design business processes in a variety of business contexts.

Pre-requisite: MBIS4004 (Co-requisite)

MBIS4009 Professional Practice in Information Systems-

Unit Description

MBIS4009 Professional Practice in Informatiom Syatems educates students about the ethical, legal and social issues that they are likely to meet as future inforamtion syatem (IS) professionals. Viewed
through the lenses of current IS practice and professional codes of ethics, these issues include data and privacy, confidentaiality, cybercrime and internet fraud. On successful completion of this unit, students will have become aware of the ethical and legal obligations within IS and will have develpoes their negotitation and conflict resolution decisions in preparation for their future role as IS professionals.

MBIS4016 Discovering Data Analytics-

Unit Description

MBIS4016 Discovering Data Analytics aims to develop students’ conceptual understanding of data analytics in the context of real-world applications. Students will learn about basic concepts, essential techniques and popular tools used in the IT industry and various aspects of data science. Students will be introduced to the lifecycle of a data science project which involves data collection, management, wrangling, analytics and visualisation. They will gain a conceptual understanding of how to identify and define data science-relevant tasks in practical scenarios and acquire the knowledge as to when to apply techniques and tools to resolve given data science-relevant tasks. Students will discuss issues of privacy, surveillance, security, classification, discrimination and decisional autonomy from a legal, ethical, and policy perspective (whether business or public policy) within areas of relevance, including health, marketing, employment, law enforcement, and education. Furthermore, students will learn to recommend to stakeholders and decision-makers based on data analytics results from the different technologies. Additionally, this unit will assist the students to prepare for the Google Data Analytics Professional Certificate.

Pre-requisite: MBIS4002 Software Development & MBIS4003 Database Management System

Exit Point: Graduate Diploma of Business Information Systems (Data Analytics)

Level 5000 (AQF 9)+

MBIS5009 Business Analytics-

Unit Description

Analytics plays an increasingly important role in determining the success of organisations in the digital age. MBIS5009 Business Analytics introduces students to the concepts and techniques that are used to leverage an organisation’s data for effective strategy and decision-making. This unit covers topics on understanding different types of data, finding relationships among attributes, and predicting outcomes by applying techniques such as regression, time series, classification and clustering. Furthermore, students will learn how to use Natural language processing techniques to analyse text from social media to understand customer feedback better.

On successful completion of this unit, students will be able to answer business-related questions by identifying and applying appropriate business analytics tools and techniques. As future managers, students will learn how to use Python and associated libraries as well as KNIME to generate insights from raw data. Students will also develop an ability to manage risks, achieve higher customer satisfaction and thereby achieve business objectives such as increased profitability, more significant market share and improved shareholder value.

Pre-requisite: MBIS4007

MBIS5001 Applied Data Analytics-

Unit Description

MBIS5001 Applied Data Analytics introduces students to techniques for extracting meaningful information from real-world datasets. This unit aims to offer students the opportunity to learn advanced aspects of data science, modern methods, techniques and applications of data science.

This subject develops an understanding of probability and statistics applied to Data Science. Students will study statistical data investigations, summary statistics, data visualisation and probability as a measure of uncertainty. It advances a range of methods, including generalised linear models, classification, advanced regression techniques and unsupervised statistical learning. Emphasis is placed on the relevance of mathematics to data science applications (such as least squares estimators and calculation of variance in data), and on the development of clear communication in explaining technical ideas.

The aim of this unit is to provide students with the opportunity to develop advanced working knowledge in statistical modeling and statistical programming. They will also learn about advanced statistical programming using the Python or R language, to perform simulation, model development, model checking, and result interpretation. Sources of this unit could be considered for the Specialist Data Scientist professional certificate (https://www.dasca.org/).

Pre-requisites: MBIS4003 Software Development & MMBIS4016 Discovering Data Analytics

MBIS5002 Data Analyst Professional-

Unit Description

MBIS5002 Data Analytics Professional aims at providing students with the opportunity to understand their profession and its environment. The role of a Data Analyst is an increasingly ubiquitous job role in many organisations of varying sizes. As well as a variety of technical skills, the practicing Data Scientist also requires knowledge and awareness of key ethical, privacy and governance considerations for managing data, and data security and related techniques for implementing such. Moreover, a Data Analyst in an organisation must be an effective communicator both with other business units and with management, displaying an ability to both understand business needs and to communicate analyses effectively to inform decision making. This unit also immerses students into the possible roles and the implications each role can have within the organisation and society.

This unit introduces the concepts related to legal, ethical, privacy, and governance issues for data collection; describes techniques for effectively managing such issues; provides you with techniques for effective communication and other considerations required of the Data Analyst in a professional organisation.

MBIS5003 PM for Designing Data Analytics Solutions-

Unit Description

MBIS5003 Project Management for Data Analytics Solutions aims at developing the student’s skills in designing effective and viable data science solutions applicable to the context of the business. Following established project management and system analysis techniques specific to data science, the student learns the required steps and methods to implement, validate and verify a solution.

This unit involves the development of a business data solution in a project team. It provides students with an opportunity to develop the knowledge and skills needed to understand systems design principles, techniques and tools in the area of data analytics. The subject integrates previous learning in data science and prepares students to address issues and challenges in data science systems design and project management. Students learn important factors that help with the successful implementation of data science projects in a given focus area.

Within this unit, students will also learn how to produce UML analysis and design diagrams, analyse and verify data science project requirements, and produce and verify UML analysis and design models. Students will also learn how to evaluate and select the most appropriate design patterns for use in a data science project solution. Sources of this unit could be considered for the Certified Analytics Professional program (https://www.certifiedanalytics.org/).

Pre-requisites: MBIS4004 Systems Analysis Design, MBIS4016 Discovering Data Analytics & MBIS5009 Business Analytics

MBIS5008 Cloud and Big Data for Data Analytics (Elective)-

Unit Description

MBIS5008 Cloud and Big Data for Data Analytics aims at providing students with the opportunity to study current state-of-the-art technologies for analysing huge amounts of data and responding to millions of user requests within one second. Currently, the most cost-efficient way of achieving the above aim is to use large-scale cloud-based services offered by vendors such as Amazon, Google, IBM and Microsoft. Students will study how to use the cloud services provided by these vendors to meet the big data needs of businesses.

This unit provides students with an in-depth study of cloud computing technologies and their use in business. It looks into various standards-based cloud systems and architectures. It further discusses various cloud delivery models and planning for migration to a cloud model. It also discusses governance and security issues in a cloud model and managing the cloud infrastructure. This subject includes the following topics: cloud architectures, parallel database systems, map and reduce, key-value stores, transaction support in the cloud, virtualization, and multi-tenant database systems, association analysis, classification and prediction, cluster analysis, and mining complex types of data. Sources of this unit could be considered for the Cloud Computing Certification Program (https://www.cloudcredential.org/certifications/cloud/).

Pre-requisites: MBIS4003 Software Development & MBIS4016 Discovering Data Analytics

MBIS5010 Machine Learning for Data Analytics (Elective)-

Unit Description

MBIS5010 Machine Learning for Data Analytics enables students to have a deep understanding of the design and implementation of analytics solutions using machine learning algorithms. From core concepts to advanced techniques, you will learn how to implement, improve and optimize parametric and non-parametric models. This subject also explores learning techniques, ethical principles in machine learning, and the state-of-art methods and tools to guide professional practice to better manage and deploy machine learning models. Students will be able to analyse data in order to draw conclusions about the given information. When it comes to techniques and processes involved, machine learning plays an important role in automating the data analysis workflow to provide deeper, faster, and more comprehensive insights.

Pre-requisites: MBIS4003 Software Development & MBIS5009 Business Analytics

MBIS5021 Systems Security Professional (Elective)-

Unit Description

MBIS5021 Systems Security Professional introduces students to the profession of a security officer in a business information systems environment. Students will analyse and apply content from the eight domains that comprise a Common Body of Knowledge (CyBOK) for information systems security professionals. This unit will also help students prepare for the Certified Information Systems Security Professional (CISSP) industry certification exam from the International Information Systems Security Certification Consortium (ISC2https://www.isc2.org/Certifications/CISSP) gaining initial recognition as an associate of ISC2.

MBIS5017 Artificial Intelligence Fundamentals (Elective)-

Unit Description
MBIS5017 Artificial Intelligence Fundamentals introduces students to fundamental concepts and different application fields of AI. The main topics include knowledge representation, searching, reasoning, expert system design, intelligent agents, responsible AI principles and applications. Practice on the design and development of AI models for real-world problems will be offered in labs.

It is aimed at forming the student to critically assess the scope of artificial intelligence theories and applications, devise appropriate representations of search problems and knowledge representation schemes, represent diverse situations using knowledge representation schemes and design and develop AI models for real-world problems. This unit in conjunction with MBIS5010 – Machine Learning for Data Analytics could be considered as training for the Artificial Intelligence Board of America (AiE) professional certification (https://www.artiba.org/certification/artificial-intelligence-certification ).

Pre-requisites: MBIS4003 Software Development, MBIS4016 Unveiling data Analytics & MBIS5009 Business Analytics

MBIS5018 Data Mining and Business Intelligence (Elective)-

Unit Description

MBIS5018 Data Mining and Business Intelligence unit is designed to equip students with the knowledge and skills to operate in an effective and professional way in applying Business Intelligence (BI) and Data Mining (DM) to suggest strategic actions to a business manager for decision-making.

This unit will help the students understand the different data types, statistical modeling, and visualisation techniques. Other specific areas covered in the unit include diverse BI applications, data mining, text and web mining, and the relationships between BI and Data Mining. Furthermore, it will enable students to generate patterns or insights from historical or current data through descriptive analytics, predict or forecast outcomes using predictive analytics and combine these to optimise business outcomes through prescriptive analytics. Upon completing this unit, students will have the opportunity to analyse and transform data into knowledge that is applicable to decision-making in an organisation. As future managers, students will learn how to convert raw data into analytics-ready data and optimise data mining models to get the best insights using KNIME. The generated insights will help the students to gain competitive advantages and enable data-driven decision-making. Overall, this unit aims to create successful managers who will use the data generated from the business to generate insights to enable data-driven decision-making using data mining and business intelligence techniques. In addition, this unit will assist the students to prepare for the Certified Business Intelligence Professionalcertification.

Pre-requisites: MBIS4008 Business Processing Management & MBIS5009 Business Analytics

MBIS5015 Capstone Project (20 CP)-

Unit Description

As well as providing students with further knowledge and skills, MBIS5015 provides the opportunity for students’ knowledge, skills and abilities gained throughout the Master of Business Information Systems programme to be applied in this Capstone Project; especially those acquired in the prerequisite unit, MBIS5012 Strategic Information Systems.

Working in small teams, students will research a real-world problem and develop creative, practical, unique and relevant solutions. They will be required to undertake research that includes the application of theory and frameworks for problem identification, justification of approach, and the development and presentation of solutions. Students will also demonstrate their communication skills, technical competence and expertise. All groups will present their project outcomes at a showcase for the industry and academic members both within and outside of the Information Systems discipline. Student projects will vary, but all will require advanced research to support project development, reflection and technical output from the project.

Pre-requisite: MBIS5012*

* Students must firstly complete 80 credit points (8 units) before they are eligible to undertake the MBIS5015 Capstone Project.

Exit Point: Master of Business Information Systems (Data Analytics)

What you will achieve

  • Create effective organisational strategies to lay the foundation for achieving success.
  • Examine both local and global business trends to consistently maintain a competitive edge.
  • Acquire essential skills in critical thinking and strategic planning within a corporate environment.
  • Recognise intelligent business prospects and comprehend how to capitalize on them.

Career Opportunities

Potential career paths

  • Data Analyst
  • Data Scientist
  • Data Architect
  • Business Analyst
  • Data Analytics Consultant
  • Data Mining Analyst
  • Data Visualisation Analyst

Entry Requirements

To view our Entry Requirements, click here.

How to Apply

To view how to apply click here.

We’re absolutely thrilled that you’re interested in discovering more about the exciting educational opportunities here at AIH! Your inquiries are most welcome, and we can’t wait to give you all the information you require. Please don’t hesitate to get in touch with us anytime you like – we’re here to help!

Further Study
Options

Completion of this qualification meets the academic requirement for admission to Doctorate courses within Australia and overseas*

*subject to additional institution/course specific requirements

Related Courses

Master of Business Administration (Business Analytics)

CRICOS Code: 111558E

Master of Project Management

CRICOS Code: 111561K

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