Why study data and technology?
The world runs on data – and so will the future. Be a part of it with a career in data and technology.
What is data and technology?
Data and technology refers to a broad and constantly evolving field where data specialists leverage information to extract meaningful insights and support decision-making. These data specialists will harness maths and statistics, computer programming, analytics, artificial intelligence (AI) and machine learning to analyse and understand the vast volumes of data being generated and collected globally every day.
And the amount of data is only growing – approximately are created each day – which means that data specialists are in greater demand than ever.
What does a career in data and technology involve?
Data specialists “make discoveries while swimming in data. … [They’re] at ease in the digital realm, they are able to bring structure to large quantities of formless data and make analysis possible,” write Thomas H. Davenport and DJ Patil for .
“They identify rich data sources, join them with other, potentially incomplete data sources, and clean the resulting set. In a competitive landscape where challenges keep changing and data never stops flowing, [they] help decision-makers shift from ad hoc analysis to an ongoing conversation with data.”
Broadly, careers in data engineering, data science and business analytics can include the collection of data from a variety of sources, organising that data for analysis, and then analysing that data using technology like business analytics platforms, predictive analytics and machine learning. Often, they’ll also need to present their findings to the rest of their business or organisation using data visualisations or reports.
They work across every sector and industry. In science, data specialists might use their skills to build predictive models to predict climate change or the spread of infectious diseases. In tech, they might analyse on-demand streaming data to make recommendations. In business, they might analyse spending patterns to make economic forecasts. The applications are endless.
What is the difference between a data engineer, data scientist and business analyst?
While data engineers, data scientists and business analysts require similar skill sets, there are differences in what each specialist does.
Data engineers develop new ways to store and access large amounts of data. They design, build and test data architecture and tools that make it easier to collect and analyse data.
Data scientists analyse and interpret raw data to find insights and patterns that provide insights and solve problems.
Business analysts work in businesses to identify opportunities and make recommendations on business strategies.
What types of data and technology jobs are available?
The demand for data experts “has raced ahead of supply” around the world, according to the Harvard Business Review. This means there are plenty of opportunities to take your data and technology career in any direction you want.
In Australia alone, the demand for data scientists is expected to grow by in the next five years, while the demand for business analysts is expected to grow by .
Jobs in data science, data engineering and business analytics include:
- Business analyst
- Business insights manager
- Chief data officer
- Computer systems analyst
- Data analyst
- Data consultant
- Data engineer
- Data scientist
- Machine learning expert
- Management analyst
- Market research analyst
- Marketing data scientist
- Statistician
