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ANZSCO Code

ANZSCO 224114 Data Analyst

A Data Analyst gathers, examines, and interprets data to support decision-making in business. They verify data accuracy, identify patterns, and communicate insights through reports and dashboards, enabling organizations to recognize opportunities and mitigate risks.

Skill Level

Level 1 or Equivalent

Specializations

Business Intelligence Analyst, Data Visualisation

Skills Assessment Authority

ACS (Australian Computer Society)

On the Occupation Lists:

Medium and Long-term Strategic Skills List (MLTSSL):

Short-term Skilled Occupation List (STSOL):

Regional Occupation List (ROL):

Not on the Occupation Lists:

State and Territory Nominated Occupation Lists:

Closely Related Core Data Units

Data Collection and Management

Data Cleaning and Preparation

Data Analysis and Statistics

Data Visualization

Database Design and Management

Business Intelligence (BI)

Predictive Analytics

Programming for Data Analysis

Additional Closely Related Core Data Units

Data Warehousing

ETL (Extract, Transform, Load) Processes

Data Mining

Advanced Statistical Methods

Data Governance and Quality Assurance

Geospatial Analysis

Machine Learning Fundamentals

Big Data Technologies

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Unit Group: 2241 Data Analyst

A role of data analyst is essential in gathering, analysing, and interpreting data to aid organisations in making decisions. They utilise data visualisation tools to develop reports and dashboards that effectively present insights in a clear and actionable manner.

Skill Level

Most occupations in this unit category require expertise equivalent to a bachelor’s degree or higher. In place of a formal qualification, at least five years of relevant experience and/or an equivalent vendor certification may be accepted. In some cases, alongside the official qualification (ANZSCO Skill Level 1), relevant experience and/or on-the-job training may also be required.

English Requirement

IELTS result with a minimum score of 6 (L, R, W), 7 in speaking and 7 overall

PTE Academic of minimum score of 50 in each section.

TOEFL iBT with minimum scores of 12 in Listening, 13 in Reading, 21 in Writing, and 18 in Speaking.

Cambridge English (CAE) with minimum score of 169 in each section.

Occupations in this Group

224114 Data Analyst

224115 Data Scientist

Tasks to Perform

Determining software and hardware requirements to provide solutions to problems

Responding to inquiries about software and hardware problems

Adapting existing programs to meet users’ requirements

Installing and downloading the appropriate software

Ensuring efficient use of applications and equipment

Implementing computer networks

Designing and maintaining websites

Repairing and replacing peripheral equipment such as terminals, printers and modems

May work in a call center

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RPL FAQs

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What is ACS RPL for ANZSCO 224114 – Data Analyst?

ACS RPL (Recognition of Prior Learning) is an assessment pathway provided by the Australian Computer Society for ICT professionals applying under ANZSCO 224114 – Data Analyst who do not hold an ICT-major or closely related qualification. This pathway allows applicants to demonstrate their data analysis skills and knowledge through professional experience and project evidence rather than relying solely on formal education. It validates the applicant’s ability to collect, process, analyze, and present data using tools and methodologies aligned with Australian ICT standards.

Who should apply through the ACS RPL pathway?

The ACS RPL pathway is suitable for Data Analysts who hold a non-ICT or partially ICT-related qualification, or those with overseas qualifications not assessed as ICT-major. Applicants must have relevant professional experience in data analysis, including data collection, data cleaning, statistical analysis, reporting, dashboard development, and data visualization aligned with the duties of ANZSCO 224114.

Is ACS RPL mandatory for Data Analysts?

No, ACS RPL is not mandatory for all Data Analysts. It is only required if an applicant does not meet the ACS educational requirements for the standard pathway. Applicants who hold an ICT-major qualification may be assessed through the standard ACS skills assessment pathway instead. Choosing the correct pathway depends on your academic background and the relevance of your qualification to ICT.

What is the structure of an ACS RPL report for Data Analyst?

An ACS RPL report consists of Key Areas of Knowledge (KAoK) responses and two detailed Project Reports. The KAoK section evaluates both core ICT knowledge and specialised data analysis knowledge, while the project reports demonstrate practical, real-world experience in working with data, using analysis tools, and producing business insights. Together, these components must prove that the applicant possesses skills and knowledge equivalent to a formal ICT qualification relevant to Data Analyst (ANZSCO 224114).

What documents are required for the ACS RPL assessment?

The documents commonly required for ACS RPL include a completed ACS RPL report (with KAoK responses and project reports), employment reference letters, a detailed CV outlining data analysis responsibilities, academic certificates and transcripts if applicable, passport and identity documents, and English language test results if required. Providing clear, consistent, and verifiable evidence is crucial for a successful assessment.

What are the Key Areas of Knowledge (KAoK) for Data Analyst?

For Data Analyst (ANZSCO 224114), the KAoK section assesses core ICT knowledge as well as specialised data analysis knowledge. Applicants must demonstrate understanding of data structures, databases, data cleaning, statistical analysis, data modeling, visualization techniques, and reporting tools. Responses should show theoretical understanding as well as practical application in real workplace scenarios.

How detailed should ACS RPL project reports be?

Project reports must be detailed and clearly describe the project objectives, business context, and your individual role as a Data Analyst. They should explain tasks such as data collection, data cleaning, analysis methodologies, tools used (such as SQL, Python, R, Power BI, Tableau, Excel), and outcomes achieved. Reports should be written in the first person and focus on the applicant’s personal contributions, highlighting problem-solving and data-driven decision-making.

Is English language proficiency required for ACS RPL?

Yes, English language proficiency may be required for ACS RPL unless exemptions apply based on nationality or education history. ACS guidelines outline specific exemptions for applicants from certain English-speaking countries or those who have completed education in English. Applicants should check the ACS requirements carefully to confirm if they need to provide test results.

Can freelance or self-employment experience be used for ACS RPL?

Yes, freelance or self-employed Data Analyst experience is acceptable if it is supported by strong evidence. This may include client contracts, invoices, payment records, client reference letters, and detailed project documentation that clearly outlines your role and responsibilities. The experience must be verifiable and aligned with ANZSCO 224114.

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