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

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

Any modern business today will utilise some form of spreadsheet tool to review, manipulate and visualise data (in the form of charts for reporting). A spreadsheet tool also enables one to undertake advanced tasks on business data, such as performing scenario analyses and undertaking complex data analytics, for example creating a forecasting model. In this subject, you will learn how to use two technological tools to undertake data analysis. The first tool is Structure Query Language (SQL), which we will use to pull relevant data into Excel and facilitate further analysis. Next, various advanced Excel analyses including pivot tables, statistical analysis, and creation of basic forecasting models will be covered. Upon successful completion of this subject you will be proficient in basic data analysis using Excel and SQL, setting you up to become an analytical and data driven problem solver. With these skills, you will also be ready to identify insights allowing you to disrupt typical business operations systematically and with a higher chance of success.

Get up to speed with basic data analysis using SQL and Excel. You’ll delve into the data analytics concepts and processes used in business today. Find, present, and explain data trends. Solve complex business problems.

This subject introduces students to modern data analytics, visualisation, and statistics. It equips students with the skills required to take advantage of powerful computing for the analysis and visualisation of complex data. These skills are used to solve problems in areas such as the biological sciences, medical sciences, agricultural sciences, nutrition, health sciences, education, and business. Students will become familiar with data visualisation and computing, descriptive statistics, statistical modelling, and data-based decision making. Using statistical computing packages is an integral part of this subject. This subject allows further study in second-year subjects in statistics and data science.

Making Sense of Data

In this subject, you are introduced to quantitative statistics, qualitative coding and the role of health data analytics in healthcare organisations and public health research. Key emphases include understanding the importance of healthcare data as an asset, identifying and applying the key elements of the data capture and analysis process in key research methodologies, along with effective presentation, communication and dissemination of findings beyond peer review publications. You will also investigate the role of health data analytics in quality and performance indicators. This subject includes synchronous sessions held during business hours. This means that you will attend sessions each week simultaneously with your facilitator and classmates. This subject is recommended for first-year undergraduate students.

Introduction to Data Analytics in Healthcare

This subject helps the student evaluate data-based evidence encountered in everyday life. It provides the fundamental numeracy skills required by business people, scientists, lawyers, nurses, journalists, social scientists, teachers and other professionals who need to evaluate data-based arguments, whether found in newspapers, television or on-line websites. This is achieved by a combination of studying newsworthy topics introduced in lectures, laboratory classes which encourage engagement with others and on-line quizzes that assess numeracy skills. The four themes covered in this subject are gathering useful data, turning data into information, probability and from data to decision making.

Companies are acquiring massive amounts of data and providing Internet-based service to millions of people. This is extremely challenging due to the large scale of data involved and the huge number of concurrent requests by users. This subject will cover the 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, Microsoft, etc. You will have the opportunity to learn how to use the cloud services provided by Amazon Web Services to meet the big data needs of businesses. The subject will also cover how to program the world’s most popular Big Data analytics framework called Hadoop with a focus on Map Reduce, Hive and Apache Spark.  This subject will also cover the following topics: cloud architectures, parallel database systems, key value stores, transaction support in the cloud, virtualization, and multi-tenant database systems.

Big Data Management on the Cloud

The ability to visualise data is one of the most useful forms of data analysis and data presentation. Data visualisation provides an accessible way to see and understand trends, outliers and patterns in data. Nowadays there are many different tools for collecting and querying data. In order to gain full benefit from the collected data we need to visualise the data. In this subject you will learn the following: how to prepare data for visualisation; the design principals for creating effective data visualisations; and how to communicate your data analysis using reports containing data visualisations. You will learn how to use state of the art software tools for generating insightful and interactive data visualisations.

Data Visualization

Traditional business models are being disrupted by numerous factors. Chief among them are new technologies that change how businesses operate. One commonality observed among these disruptive trends is the role of data. Data has become a highly valued business asset, forming a strong foundation to high quality decision processes. This subject will introduce you to the role of data in disrupting traditional business operations and formulating business strategy. You will gain an appreciation of how data can be turned into business insights through a process called analytics, using examples across a range of business problems. On completion of this subject, you will appreciate the pivotal role that data and analytics play in various strategic initiatives within organisations, and the strategies that link analytics to business performance while balancing issues such as ethical and data governance.

La Trobe University Data analytics Short courses | Open Universities Australia

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