The Master of Business Information Systems (Data Analytics) is designed for professionals who wish to gain advanced technical skills and expertise in areas of data science and analytics. As a business professional or ICT specialist, graduates not only understand how to analyse datasets but also interpret the data and source the most relevant data which can be incorporated into the organisational business decision-making system in a way of offering recommendations to decision-makers and managers.
Master of Business Information Systems (Data Analytics)
|Duration: 2 years full time|
|Assumed Knowledge: nil|
|Course Intake: January, February, March, May, June, July, August, September, October, November|
WHAT YOU’LL LEARN
To complete the degree, you will need to pass ﬁfteen Units (160 credit points). These units are delivered over two years. There are 13 units that are compulsory and 2 units which are electives. The units and their descriptions are listed below. . The units and their descriptions are listed below.
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.
A Master Course is awarded after completing 15 units of study. Students wishing to exit with a Graduate Certiﬁcate of Business Information Systems may do so after the successful completion of 4 units. A Graduate Diploma of Business Information Systems (Data Analytics) requires 8 units for completion.
As a student, you will need to allocate time to attend classes. Generally, if you are studying full-time, you will have 12 hours of classes each week (for 4 units), on-campus. 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, projects, workshop preparation and to prepare for tests and exams.
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
- Practical assessments
- Discussion forums
- Participation in class including formative assessment activities
- Demonstrate an advanced and integrated comprehension of business information systems (Data Analytics) theory and
- Investigate and design creative IS solutions for complex businesses.
- Research and critically evaluate the eﬀectiveness of business information systems (Data Analytics) within speciﬁc.
- Provide business information systems (Data Analytics) recommendations to relevant.
- Exhibit Leadership, management, and interpersonal skills required by diverse teams working on business information.
- Apply knowledge and skills in response to current ethical dilemmas and professional issues in business information.
AQF LEVEL 9
|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.|
Graduates at this level will have expert, specialised cognitive and technical skills in a body of knowledge or practice to independently:
|Graduates at this level will apply knowledge and skills to demonstrate autonomy, expert judgement, adaptability and responsibility as a practitioner or learner.|
Source adapted from https://www.aqf.edu.au/aqf-levels
WHAT UNITS YOU'LL STUDY
Semester 1 – 4 core units
MBIS4001 Information Systems Applications in Business
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
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
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
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.
Semester 2 – 4 core units
MBIS4007 Big Data and Visualisation
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
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
MBIS4009 Professional Practice in Information Systems educates students about the ethical, legal and social issues that they are likely to meet as future information system (IS) professionals. Viewed through the lenses of current IS practice and professional codes of ethics, these issues include data and privacy, confidentiality, 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 developed their negotiation and conflict resolution skills, as well as their critical thinking skills sufficient to make ethical and professional decisions in preparation for their future role as IS professionals.
MBIS4016 Discovering Data Analytics
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
Semester 3 – 4 core units
MBIS5009 Business Analytics
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.
MBIS5001 Applied Data Analytics
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
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
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
Semester 4 – 1 core unit (double) and 2 out of the below 4 elective units
MBIS5008 Cloud and Big Data for Data Analytics (Elective)
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)
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
MBIS5017 Artificial Intelligence Fundamentals (Elective)
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)
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 Professional certification.
Pre-requisites: MBIS4008 Business Processing Management & MBIS5009 Business Analytics
MBIS5015 Capstone Project (20 CP)
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.
* Students must firstly complete 80 credit points (8 units) before they are eligible to undertake the MBIS5015 Capstone Project.
|Duration: 2 years full time|
|Assumed Knowledge: nil|
|Course Intake: January, February, March, May, June, July, August, September, October, November|