Your career
The explosion in device connectivity and increasing data volumes, combined with the rise of the Internet of Things and the impact of social media, are all factors fuelling exponential growth in big data and data analytics. The digitisation of industries and the sheer volume of data being collected is not showing any signs of slowing. As businesses harness the power of data to remain competitive, demand for data analysts who can effectively extract, translate, visualise, and communicate information is soaring. The boom in big data, machine learning and artificial intelligence means demand is peaking for these specialists globally.
Data analytics is not just reserved for big tech giants. Traversing areas such as health, education, retail, telecommunications, financial services and management consulting, data analysts are needed in almost every industry, opening a world of opportunities for your career.
A UniSA Online Data Analytics degree can help you pursue the following careers:
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Data analyst: Conduct pre and post-campaign analysis, identify targeting opportunities that support decision making across promotional campaigns; work with datasets or big data environments such as SQL Server, AWS Athena or Presto; demonstrate proficiency in Excel, SQL and scripting languages such as R or Python; create dashboards and data visualisations using tools such as Tableau or Microsoft PowerBI; design and drive analytical experiments and make recommendations based on results; communicate data insights to both analytical and non-analytical stakeholders.
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Data scientist: Identify relevant data sources for business needs; collect and organise large amounts of data into usable formats; solve business-related problems using data-driven techniques; build predictive models and machine learning algorithms; work with a variety of programming languages including SAS, R and Python; keep-up-to-date with analytical trends and techniques such as machine learning and text analytics; generate insights from data sets and identify trends and patterns, and effectively communicate data findings to technical and non-technical audiences.
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Business data strategist: Assess the most effective operating model and data approach to achieve business objectives; define and drive the enterprise-wide analytics vision across strategy, people, process, data and technology; and be heavily involved in business transformation, change and education needed to embed analytics into the organisational culture.
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Data engineer: Develop new ways to store and access large amounts of data; design, build and test data architectures and tools that enable easier access and interpretation of data in a business context; develop, construct, test and maintain IT architectures such as databases and large-scale processing systems; gather, process and transform raw data from different sources and third parties; and extract data from systems to develop insights and recommendations that inform business decisions.
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Data architect: Set up data platform technologies to manage and secure the flow of structured and unstructured data from multiple sources; create and maintain an optimal data pipeline architecture; develop reusable, maintainable and scalable data integrations and services; install and configure information systems; migrate data from legacy systems to new software solutions; design conceptional and logical data models and flowcharts; improve system performance by conducting tests and troubleshooting new elements.
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Data visualisation specialist: Use visualisation tools and software to communicate information in different ways; present data in a way that is easy to understand, and spot patterns, trends and correlations; transform, improve and integrate data depending on business requirements; combine data sets across multiple sources; and deliver data in a useful and appealing way to users.
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Information analyst: Provide advice, analysis and interpretation of data and information to key senior stakeholders; test security systems and identify potential problems that could cause security breaches in computer systems, mobile apps, and cloud software; write detailed risk reports if potential threats are discovered; develop security plans to protect system data; put up firewalls to guard data and protect systems from potential dangers; possess expert knowledge of the networking technologies within the organisation; demonstrate advanced programming skills in C, C+, and Java.
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Reporting analyst: Analyse metrics and design reports to help drive critical business decisions; communicate results to senior stakeholders and provide recommendations based on the findings; design business analysts and data recording systems for the organisation; maintain databases and perform updates to ensure data accuracy; collect and analyse data for various types of business reports; monitor data to identify changes in financial and business trends.
Conclusion: So above is the Bachelor of Data Analytics article. Hopefully with this article you can help you in life, always follow and read our good articles on the website: W Tài Liệu
