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Study online with University of Tasmania through Open Universities Australia. Explore all degrees, subjects and short courses now.

Learn to use data to make informed business decisions. A Bachelor of Business majoring in Business Analytics will include building foundational programming skills for business analytics and developing knowledge on the business context and various applications of analytics in a range of business scenarios. Business analytics is an exciting and emerging discipline that combines technology-related skills with business acumen.The Business Analytics major aims to provide students with an understanding of the impact, potential and limitations of business analytics for businesses in today’s data-driven world. The major develops a range of skills and competencies that enhance existing skills common to business professionals and develop new skills that are now considered necessary for business professionals. Business Analytics is positioned at the intersection of business and Information, Communications and Technology (ICT). As such ICT-related skills will be developed and applied with a specific focus on application for businesses by business professionals, along with the development of other skills relevant to business analytics such as critical thinking, problem solving, communication and teamwork. The Business Analytics Major is relevant for all business professionals due to the ubiquity and proliferation of data and the significant potential of the wealth of data to provide businesses with a competitive advantage.

Choose a business degree that empowers you with one of the most important skills in business today: data analytics. Graduate with skills that put you at the forefront for tech-driven roles. Learn how to make business decisions based on data.

Bachelor of Business (Business Analytics)

Data and Analysis

Data Analytics Concepts

Business Intelligence

Scientific Computing

Data Analytics for Cyber Security

Data Visualisation

Data-Based Critical Thinking

HR Analytics

Professional Practice in Data Analytics

Disruption in Business

In this subject, you will be introduced to mathematical and statistical methods for analysing scientific, business or technical data to inform and support decision-making. You will explore why data is needed and how it is used to make decisions, including how data are collected, analysed, interpreted and presented, and you will learn and apply a suite of common statistical and mathematical methods to generate evidence for decision-making.You will also be introduced to data management software and learn how to represent and communicate mathematical and statistical information effectively. Through data sets relevant to your discipline, you will learn how to problem solve, generate evidence, and present solutions using data handling and statistical approaches.

In this subject you will learn about three key areas of data analytics in cyber security. Using a series of tools to develop your cyber security analytical tool kit, you will begin by conducting basic data analysis using Excel and build an analytical dashboard in Excel which will allow you to dynamically update the dashboard based on the dataset entered. With these skills you will then transition to network data analytics for threat hunting and incident response, culminating in an assessment on post-infection threat analysis. Finally, you will undertake active network monitoring and analysis using cutting edge industry tools, that will form your final assessment. The progression of practical skill development in this subject will add progressive complexity to your understanding of data analytics scoped to cyber security and align with a Security Operations Centre (SOC) analyst&#39;s role.

Learn how to collect, analyse, and present data for cybersecurity. You’ll explore analytical techniques and tools that identify patterns, anomalies, and potential security breaches. Harness the power of data to protect organisations from cyber threats. 

In this subject, you will be introduced to mathematical and statistical methods for analysing scientific, business or technical data to inform and support decision-making. You will explore why data is needed and how it is used to make decisions, including how data are collected, analysed, interpreted and presented, and you will learn and apply a suite of common statistical and mathematical methods to generate evidence for decision-making.You will also be introduced to data management software and learn how to represent and communicate mathematical and statistical information effectively. Through case studies relevant to your discipline, you will learn how to problem solve, generate evidence, and present solutions using data handling and statistical approaches.

Use data to make decisions in business, science, and technology. You’ll learn how to collect data, interpret it, and present it. Get to know statistical techniques and software. Communicate results clearly. Present solutions with confidence.

In this subject you will focus on the evaluation of quantitative information, in both everyday and academic situations. This subject will introduce you to research methodologies and frameworks to assess the reliability of online data sources. You will learn how to analyse and interpret numerical data and critically evaluate standard presentation methods, including column charts, line graphs, histograms, boxplots, scatterplots, and pie charts. You will also learn how to make informed decisions based on quantitative evidence and communicate your conclusions in a formal report style.

Numeracy and Data in Practice

In today’s data economy, businesses are blessed and cursed with an abundance of data. This proliferation of data is creating new professions and changing existing professions. One profession that is witnessing a rapid change due to the explosion of data is accounting. While there exists a plethora of data available to businesses, accounting data remains a source of data that is reliable, relevant and accessible for all organisations. This subject will introduce students to the very recent changes ushered in by the big data revolution to the accounting profession, introduce students to how data analytics is being applied to accounting data, develop their skills in analysing and presenting accounting data to management and also develop their abilities to critically evaluate the underlying accounting systems and processes related to both the collection, creation, processing and production of accounting data within organisations.

Data Analytics for Accounting

This subject will enable students to critically evaluate the theory, practice and processes for managing data in the healthcare system. The foundations of health data, information, knowledge and wisdom will be introduced, including the concept of information architecture. Methods and the value of data analysis and interpretation are the central focus of the subject, along with an exploration of the role of data linkage. Students will have opportunities to hear from experts across Australia and participate in industry case studies and analyses.

Health Information Analysis and Improvement

Students will acquire the skills and techniques required to analyse and manage data, interpret results, and report data analysis methods and findings in a business environment. Qualitative and quantitative research approaches are examined to consider their respective contributions, discretely and in combination, to knowledge development through empirical research. The quantitative component covers basic statistical thinking and data analysis techniques.A strong emphasis will be placed on the logic underlying statistical concepts such as probability and probability distributions, normal distribution, sampling distributions, parameter estimation, and hypothesis testing. A range of data analysis techniques will also be covered, including t-test, Analysis of Variance, cross tabulation, regression, correlation, and factor analysis. There is a strong emphasis on the application of statistical techniques to practical research problems in a business context.The statistical computer package SPSS will be used for the statistical analysis of data. The qualitative component examines principles and techniques for organising, analysing and reporting qualitative data. The central principle of this component is the execution of rigorous qualitative data analysis through ‘good housekeeping’ –undertaking, recording and demonstrating careful, rational decision-making in qualitative data analysis (Marshall, 1999). Consequently, strategies for undertaking and reporting analysis of qualitative data are equally emphasised. Strategies for data analysis will include techniques for organising, searching, retrieving and interpreting qualitative data to develop and test theoretical conclusions.Strategies for reporting analytical processes will incorporate techniques for recording and describing data analysis, including the articulation of theoretical conclusions and the use of qualitative data to illustrate and support conclusions drawn. Data analysis processes will be undertaken using NVivo, a computer software program for qualitative data analysis.

Data Analysis and Management

With the explosion of technology and data in health, the field of health informatics is growing. This subject will evaluate the field of health informatics as a discipline within the health system, and appraise key principles and theories. The foundational elements of data, information, knowledge and wisdom are assessed within the healthcare context. Applicable standards and governance are introduced. This subject provides the foundation for ongoing exploration of health informatics.

Introduction to Health Information Management

University of Tasmania Data analytics Courses & Degrees | Open Universities Australia

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