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Online Graduate Diploma or Certificate in Business Analytics Course structure

Curriculum Details

8 subjects required

You can complete the online Graduate Diploma in Business Analytics in just one year if you study full time. Many students graduate within 14 months, but you may take up to five years to complete the course if your schedule becomes challenging.

A Graduate Certificate in Business Analytics is also available. You can complete the certificate with four subjects in six months.

For more information about the duration of the course or the course structure, speak with an enrolment advisor at (+61 3) 9917 3009 or request more information now.

Graduate Certificate in Business Analytics

Credits

This subject introduces you to business and data analytics with a strong focus on practical outcomes that are directly applicable to business contexts. It delivers a comprehensive understanding of current theories, frameworks, applications and technologies that support modern data-driven decision-making process. You will gain hands-on experience in IBM Cognos, SAP Lumira and Microsoft Power BI to design and develop analytics solutions. The subject focuses on introducing key descriptive analytics topics, data wrangling, text processing and data ethics. Industry-based guest lectures will present fresh perspectives on the managerial role in planning and implementing business analytics initiatives and the emerging role of analytics in business performance management. Upon completion, you will be able to transform business problems into analytics solutions, understand key issues, analytics frameworks, techniques, determine business value of analytics outcomes and appreciate its role in BPM.

This subject introduces you to the various techniques of data wrangling with a strong focus on hands-on experience in R and Structured Query Language (SQL) programming. It will cover the basic concepts in relational database design including Entity Relationship (ER) modelling and SQL as a tool for basic data wrangling. You will also learn various types of data sources and common data formats. The subject teaches you R programming language for you to perform data wrangling tasks, including data import and export, basic data integration and data assessment. Upon completion, you will be able to perform a variety of data wrangling tasks using SQL and R for different kinds of data types.

As data becomes ever more complex to analyse, the need for tools to help integrate the user’s knowledge and inference capability into the analytical process becomes important. In analytics, this is generally referred to as visualisation, which this subject will cover in detail from various perspectives, for example, temporal, spatial, spatial-temporal, multi-variate, text/documents, graphs and networks, and more. These perspectives will be covered with various business applications in mind including, statistical and summary reporting, trends spotting and projections, process capture, and real-time reporting. These applications will be discussed with reference to various visual analytics frameworks and theories as well as case examples.

Data-driven decision making will be an increasingly important topic in business in the coming years. Non-analytics business professionals will need to work with analytics professionals to derive business value, and vice-versa.

In this subject, you will develop selected hard and soft skills necessary for successful analytics in practice, from the perspective of both non-analytics business professionals and analytics professionals.

Furthermore, you will address competencies such as Issue Identification, Problem Structuring, Method Selection, Data Gathering, Conducting Analysis, Developing Conclusions and Recommendations, Structuring Written Materials, Oral Communications, and Presentation Skills. You will also build competencies such as Visualising Data and brief third parties regarding desired analytics.

You will learn and experience these skills through a real-world project, either focused on our local community or a business.

Graduate Diploma in Business Analytics

Credits

This subject introduces you to business and data analytics with a strong focus on practical outcomes that are directly applicable to business contexts. It delivers a comprehensive understanding of current theories, frameworks, applications and technologies that support modern data-driven decision-making process. You will gain hands-on experience in IBM Cognos, SAP Lumira and Microsoft Power BI to design and develop analytics solutions. The subject focuses on introducing key descriptive analytics topics, data wrangling, text processing and data ethics. Industry-based guest lectures will present fresh perspectives on the managerial role in planning and implementing business analytics initiatives and the emerging role of analytics in business performance management. Upon completion, you will be able to transform business problems into analytics solutions, understand key issues, analytics frameworks, techniques, determine business value of analytics outcomes and appreciate its role in BPM.

This subject introduces you to the various techniques of data wrangling with a strong focus on hands-on experience in R and Structured Query Language (SQL) programming. It will cover the basic concepts in relational database design including Entity Relationship (ER) modelling and SQL as a tool for basic data wrangling. You will also learn various types of data sources and common data formats. The subject teaches you R programming language for you to perform data wrangling tasks, including data import and export, basic data integration and data assessment. Upon completion, you will be able to perform a variety of data wrangling tasks using SQL and R for different kinds of data types.

As data becomes ever more complex to analyse, the need for tools to help integrate the user’s knowledge and inference capability into the analytical process becomes important. In analytics, this is generally referred to as visualisation, which this subject will cover in detail from various perspectives, for example, temporal, spatial, spatial-temporal, multi-variate, text/documents, graphs and networks, and more. These perspectives will be covered with various business applications in mind including, statistical and summary reporting, trends spotting and projections, process capture, and real-time reporting. These applications will be discussed with reference to various visual analytics frameworks and theories as well as case examples.

Data-driven decision making will be an increasingly important topic in business in the coming years. Non-analytics business professionals will need to work with analytics professionals to derive business value, and vice-versa.

In this subject, you will develop selected hard and soft skills necessary for successful analytics in practice, from the perspective of both non-analytics business professionals and analytics professionals.

Furthermore, you will address competencies such as Issue Identification, Problem Structuring, Method Selection, Data Gathering, Conducting Analysis, Developing Conclusions and Recommendations, Structuring Written Materials, Oral Communications, and Presentation Skills. You will also build competencies such as Visualising Data and brief third parties regarding desired analytics.

You will learn and experience these skills through a real-world project, either focused on our local community or a business.

The information age has combined with the widespread adoption of digital technology to turn information into a key business asset. Organizations now have access to massive volumes of data from diverse sources and require skills and expertise in making sense of this information for strategic decision making. Predictive analytics refers to a variety of statistical and analytical techniques used to develop models that predict future events from data. This subject will provide you with the knowledge and skills to build and use predictive models in real business scenarios. You will be given the opportunity to gain hands-on experience with one of the globally most widely used predictive analytics software tools. Case studies such as target marketing and customer churn analysis will be used to demonstrate the business value of predictive analytics. A number of related data mining and machine learning techniques such as neural networks, decision trees, customer segmentation and profiling will also be taught. The effect of big data, stream analysis and text analytics on traditional predictive techniques will also be discussed.
IT projects involve multiple stakeholders with competing interests, operate in dynamic business environments and must deliver projects in increasingly short time-frames. In this subject you will examine the foundations of project management involving scope, cost, time, human resources, procurement, risk, quality, communication and integration in the context of information systems projects and methodologies. Management techniques to effectively respond to the organizational, political and cultural barriers IT projects typically face will be discussed. Risk and stakeholder analysis, and critical chain scheduling will be taught. You will also consider advanced topics like project governance, management of cross-organisational projects, societal issues, ethics, teamwork issues, project office functions and project management toolsets. The agile project management concepts and development are also discussed.
Humans have become information triggering and transmitting ‘devices’ due to the use of ATMs, credit cards, telephones, loyalty cards, call centres, digital television, internet etc. Using customer analytics, such information can be used by organizations to understand their customer lifestyles, life stages, personal values and financial status, which helps to gain new customers, keep existing customers longer and increase the frequency and value of customers thus becoming more competitive and profitable. Social media now plays a significant role in the customer relationship both as a way of marketing products and services and also a medium through which customer segments and sentiments could be captured. Ability to efficiently make use of social media information is now becoming an essential part of customer analytics. This unit provides the necessary knowledge and skills to use data analytics technologies to better understand customers resulting in happier, content and loyal customers leading to a better customer relationship. Case studies will be throughout to concepts, techniques and tools.
Organisations are rapidly migrating technology infrastructure and applications into cloud platforms, due to increased availability, security, reliability and cost-effectiveness. Moreover, cloud platforms are crucial in enabling artificial intelligence, big data analytics and data engineering of Internet of Things, social media data streams and multimedia data. In response, these platforms are gradually becoming user-centric and customisable to suit the technology requirements of small to large scale organisations. Technical knowledge, practical skills, and IT security implements in cloud platforms are a strategic advantage in the modern workplace. This subject aims to develop a suite of technical knowledge and practical skills required to instantiate, configure, secure and manage a cloud platform for organisational needs, followed by how to leverage a cloud platform and its components for business automation, security risk management, robotic process automation, data integration and data analytics and artificial intelligence applications.

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