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

Learn to use your digital skills to analyse, interpret and present data to inform marketing strategies and tactics. Develop the know-how, the experience and the insights to be able to operate in this fast-paced industry. As the focus and importance of big brands understanding the data that drives their customers increases, so too will the demand for marketers skilled in the area of understanding the data and making data-driven decisions and drive real business change. Explore topics such a consumer behaviour, developing marketing strategies, using analytics to inform marketing tactics, and understanding more about marketing tools and technologies.

Dive deep into marketing on digital channels including social media, email, and apps. You’ll build valuable data skills for more informed analysis and tactics. Includes foundational business courses on leadership and economics.

Master of Business (Digital Marketing)

Data Analytics Concepts

Data Analytics for Cyber Security

Professional Practice in Data Analytics

UO R for Data Analytics

Mathematics Essentials in Data Analytics

Fundamentals of Mathematics for Data Analytics

Advanced Topics in Data Analytics

Data Analytics for Accounting

The Search for Everything: data Analytics and Storytelling in the 21st Century

Data Analytics: Transform

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 organizations. 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.

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

The ability to make sound decisions in High Performance Sport is critical to maximizing performance outcomes. In order to do this, practitioners need specific knowledge and skills in data analysis techniques, in addition to the ability to present data in a meaningful way to a variety of audiences. This subject is based on contemporary data analysis techniques focusing on determining practically meaningful differences in athletic performance. A range of approaches will be explored to allow for analysis of both individual and group data. The aim of this subject is to provide students with the knowledge, understanding and skills to analyse and interpret data of relevance to sports science and athletic performance and effectively present the results.

Data Analysis and Interpretation for High Performance

This is the third in the suite of professional experience subjects and includes both a theory and a practical component. This subject focuses on principles, processes and impacts of learning environment, school level and system data collection, analysis and interpretation. Data relevant to Indigenous educational outcomes will be interrogated, emphasising an evidentiary approach to program and policy development in learning environments, schools and beyond. The professional experience practical assessment is a four week full-time block placement intended to enable practical application of the knowledge and skills gained. All required clearances to work with children must be obtained and valid, and all other professional experience requirements met. Both theory and practical components must be passed in order to pass the unit.To view the Professional Experience Calendar, please see below:<a href="https://www.open.edu.au/-/media/degree-advice/2024-curtin-master-of-teaching-professional-experience-dates" target="_blank" style="background-color: rgb(255, 255, 255);">2024 Master of Teaching Prof Exp Calendar</a> (PDF)Please Note: If it’s your first time studying a Curtin University subject you’ll need to complete their compulsory ‘Academic Integrity Program’. It only takes two hours to complete online, and provides you with vital information about studying with Curtin University. The Academic Integrity Program is compulsory, so if it’s not completed your subject grades will be withheld.Find out more about the <a href="https://academicintegrity.curtin.edu.au/" target="_blank">Academic Integrity module</a>.

Professional Experience 3: Using Data to Inform Teaching and Learning

This subject was previously known as INFM120 Technologies for Information Services.Learn what is meant by big data, data science, data analytics and data-driven decision-making. This subject introduces students to the ways data can be used to answer questions, tell stories, and support strategic decision making in their discipline and professional area. Upon successful completion of the unit, students will have developed their knowledge and skills to become confident and critical users of big data tools and resources. The subject covers how to evaluate data sources, why it is important to ask questions about what is in data sets, who owns them, and what they don’t include. It will also provide students with an informed understanding of how they can capture and use data in an ethically and socially responsible manner. Hands-on learning activities focus on data gathering, processing, cleaning, presentation and reporting techniques.﻿Please Note: If it’s your first time studying a Curtin University subject you’ll need to complete their compulsory ‘Academic Integrity Program’. It only takes two hours to complete online, and provides you with vital information about studying with Curtin University. The Academic Integrity Program is compulsory, so if it’s not completed your subject grades will be withheld.Find out more about the <a href="https://academicintegrity.curtin.edu.au/" target="_blank">Academic Integrity module</a>.

Telling Stories with Data

This subject provides students with the fundamental and advanced concepts, tools and skills needed to understand the emerging role of business analytics and operations research in organizations. Emphasis would be given to problems in maritime logistics and transport, retailing and procurement. It allows students to understand and apply advanced business analytics tools in a computer-intensive environment and to communicate with analytics professionals to effectively use and interpret analytical models and results for better decision making. There is a descriptive, predictive and prescriptive approaches offered in the subject. Along with this, it discusses the fundamentals and advances of operations research as a discipline area related to simulations and decision-making processes using intelligent methods.

Business Analytics and Operations Research

Marketing decision-making is growing in importance in the business world. More than ever before, organisations are placing greater emphasis on the marketers&#39; ability to evaluate, anticipate, and illustrate the contribution of marketing to organisational performance. Increasingly, senior managers are requiring greater rigour and accountability for investments in marketing activities. Within marketing, there is a realisation that practitioners need to be able to justify their strategies, tactics and the associated outcomes, using relevant metrics. Marketing analytics seeks to build a link between the marketing activity of the organisation and the outcomes that result from it.The focus of this subject is on developing, analysing, and evaluating appropriate models to measure the performance of marketing activities. It will develop students&#39; knowledge of key strategic and technical decision-making models and metrics that form the foundation of marketing analytics. Students will gain knowledge and skills to predict the outcome of marketing plans in order to boost return on marketing investment.

Marketing Insights into Big Data

Managers need an understanding of statistics for five key reasons: to properly collect, present, describe and interpret information; to draw valid conclusions from incomplete data - typically about large populations based only on information obtained from samples; to obtain reliable forecasts; to improve business processes and; to provide a framework for dealing with risk and uncertainty. These five reasons form the basis of the structure and content of Data and Business Decision Making. The use of mathematics and arithmetical calculations are kept to a minimum for selected topics by using the Microsoft Excel spreadsheet package. The subject focuses on the interpretation and application of the various techniques studied.

Data and Business Decision Making

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