Data Analyst

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Decision Support Analyst
Medical & Health Care Analyst
Operations Research Analyst
Organisation & Methods Analyst

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   Clerical or OrganisingAnalytic or ScientificSkill Level 5Skill Level 6
Emerging Job

 Data analysts collect and analyse numerical information and present results. All companies collect data (now often referred to as 'big data'), and a data analyst's job is to take that data and use it to help companies make better business decisions or enhance customer services. Future Growth Very Strong

The main goal of a Data Analyst is to help organisations identify ways of reducing costs and find opportunities for growing revenue. Data Analysts use standard methods to collect and analyse data. They translate statistics into meaningful business information and report on their findings.

Data has changed the face of our world over the last ten years. The numerous emails, text messages we share, YouTube & TikTok videos we watch are part of the nearly 2.5 quintillion bytes of data generated daily across the world. Businesses, both large and small, deal with massive data volumes, and a lot depends on their ability to glean meaningful insights from them. A data analyst does precisely that. They interpret statistical data and turn it into useful information that businesses and organizations can use for critical decision-making.

Organizations in all sectors are increasingly depending on data to make critical business decisions like which products to make, which markets to enter, what investments to make, or which customers to target. They are also using data to identify weak areas in the business that need to be addressed.

As a result, data analysis has become one of the highest in-demand jobs worldwide, and data analysts are sought after by the world’s biggest organizations. Data analyst salary and perks only reflect the demand of this job role which is likely to keep growing in leaps and bounds.


What Is Data Analytics? - An Introduction (Full Guide)
https://youtu.be/yZvFH7B6gKI

 

 

ANZSCO ID:  261111

Specialisations: Types of Data Analysts:

  • Medical and Health Care Analyst: [below] use data from a number of sources to assist improve healthcare outcomes. They typically concentrate on the business side of medicine, increasing patient care or simplifying operations.

  • Climate Change Analyst: [on separate page]:research and analyse data relating to climate change, and develop policy documents designed to help prevent further climate change or reduce the effects of climate change. Climate change analysts create mathematical models to predict environmental changes. Their work is used to educate and inform policy and planning surrounding climate change, renewable energy and energy efficiency.

  • Market Research Analysts [on separate page]: collect and evaluate consumer and competitor data. Market research analysts investigate market circumstances in order to assess future sales of a product or service. They assist businesses in determining what items customers desire, who will buy them, and at what price.

  • Business Analyst: [below] Data is used by business analysts to create business insights and advocate improvements in corporations and other organisations. Business analysts may detect problems in almost any aspect of a business, including IT processes, organisational structures, and employee development. As companies are constantly striving to improve their overall efficiency and save expenses, business analytics is gradually becoming an essential component of their operations.

  • Business Intelligence Analyst: (BI analyst) [below] analyses data and other information to assist firms in making effective business choices. They may collect, clean, and analyse data such as a company's revenue, sales, market intelligence, or consumer engagement indicators. BI analysts may also be required to create tools and data models to aid in the visualisation or monitoring of data.

  • Operations Research Analyst [below] are high-level issue solvers that employ sophisticated problem-solving approaches such as optimization, data mining, statistical analysis, and mathematical modelling to provide solutions that help firms and organizations function more efficiently and cost-effectively.

  • Intelligence & Policy Analyst [on separate page]: Analysts of intelligence examine information and data in order to identify and mitigate security concerns. Internal and external statistics, databases, and field reports are examples of information sources. To synthesise information and generate action plans, analysts must have good research, comprehension, and analytical abilities.



  

Knowledge, skills and attributes

To become a data analyst, you would need:


  • a high level of mathematical ability
  • good IT skills
  • the ability to analyse, and interpret data
  • strong problem-solving skills
  • excellent verbal and written presentation skills
  • strong attention to detail, and a methodical and logical approach
  • the ability to plan work and meet deadlines.

Data Analyst
(Source: Simplilearn)

 

Duties and Tasks

As a data analyst, you might:

  • code and re-code data or big data to identify patterns
  • conduct data analyses using statistical or other software programs
  • formulate presentations, reports and recommendations
  • present documents in an accessible and unambiguous way

 

Did You Know?
(Source: TechTarget)
Unit Abbreviation Approximate size
bit b binary digit, a single 0 or 1
byte B 8 bits
kilobyte KB 1024 bytes or 10/\3 bytes
megabyte MB 1024KB or 10/\6 bytes
gigabyte GB 1024MB or 10/\9 bytes
terabyte TB 1024GB or 10/\12 bytes
petabyte PB 1024TBor 10/\15 bytes
exabyte EB 1024PB or 10/\18 bytes
zettabyte ZB 1024EB or 10/\21bytes
yottabyte YB 1024ZB or 10/\24 bytes

Working conditions

As a data analyst you would generally work standard hours, and occasionally longer to meet project deadlines. Your work would normally be office-based. You would use a computer and statistical software to collect, analyse and interpret data.

You can also work from home.

Working from home
(Source: Career Foundry)

Tools and technologies

Sourced from Simplilearn:

SQL: is widely used for data analysis in major corporations, and it is regarded as one of the most important tools for analysts. SQL is also used in software development by software engineers. SQL is a computer language that was designed to manage data from relational databases. It is a simple tool to learn and may be used for complicated, difficult data analyses. It is a popular option among data analysts since the code is simple to read and comprehend, and it can be used to edit and update data. Furthermore, it allows you to compile data in a way similar to Excel, but over enormous datasets and across numerous tables at once. SQL
Microsoft Excel: Excel, a data analysis industry standard, is the most important tool to master as a data analyst. It is a simple application to learn, and data analysts should be adept in all parts of Excel, from formula to pivot tables. Any spreadsheet application will work, although Microsoft Excel is the most popular. Excel
SPSS: Analysts frequently require a statistical analysis programme such as SPSS in addition to the instruments listed above. SPSS is an excellent choice for freshly certified analysts SPSS
VBA: Visual Basic for Applications - may be required by more experienced data analysts. It is a programming language built exclusively for Excel and is frequently used in financial analysis. It is also Word and PowerPoint compatible. Matlab is another excellent tool for creating algorithms, building models, and analysing data. VBA
Jupyter Notebooks: Project Jupyter is a one-of-a-kind service dedicated to the development of open-source software, open standards, and interactive computing services. It is compatible with a wide range of programming languages. As an open-source online tool, Jupyter Notebook allows you to create and share documents that may contain live code, equations, graphics, and narrative prose. The notebook may be used for a variety of purposes, including data cleansing and transformation, machine learning, and more. Jupyter
R: The open-source programming language R, which is compatible with all platforms (Windows, Mac OS, and Linux), is another important and widely used tool in data analytics. It is widely used by statisticians for statistical modelling because it provides a wide range of statistical and graphical options, and it is frequently used to undertake data wrangling. It allows the data analysts to create data visualisations such as plots and graphs and is accessible in a variety of libraries such as Plotly. It's employed in banking and sales, as well as several scientific sectors including medicine and technology. To use this data analysis tool, you must have a basic understanding of statistics and programming in general. R
Tableau: is another application that is often used by data scientists. It is widely utilised since data can be evaluated fast with it. Dashboards and spreadsheets are also created for visualisations. Tableau enables the creation of dashboards that deliver actionable information and propel a business ahead. When configured with the appropriate underlying operating system and hardware, Tableau products always run in virtualized environments. Tableau
SAS: (Statistical Analysis System) is a well-known commercial suite of business intelligence and data analytics tools. The SAS Institute created it in the 1960s, and it has evolved since then. Its primary applications now are client profiling, reporting, data mining, and predictive modelling. Designed for the business market, the software is often more robust, adaptable, and user-friendly for large enterprises. This is due to the fact that they have differing amounts of in-house programming competence. SAS
Microsoft Power BI: is a relative newcomer to the market of data analytics tools, having been around for less than a decade. It originated as an Excel plug-in before being updated as a full suite of corporate data analysis tools in the early 2010s. Power BI helps users to quickly and easily generate interactive visual reports and dashboards. Its key selling point is its excellent data connectivity—it works well with Excel (as one would expect from a Microsoft product), but also with text files, SQL servers, and cloud sources such as Google and Facebook analytics. BI

 

Education and training/entrance requirements

To become a data analyst, you will need to complete a bachelor's degree, usually in mathematics, statistics, engineering or economics. To get into these courses you usually need to gain your senior secondary school certificate or equivalent. English and mathematics would be appropriate subjects to study prior to university.

Employment Opportunities

Employment of data analysts is projected to grow more strongly than the average for all occupations.

The growth in ‘big data’ is leading to an increased focus in many businesses on analysis to apply innovative, relevant and advanced analytics techniques to support data-driven decision making.

This is particularly strong in customer centric businesses in industries such as financial services, retail, airlines, and information technology services. However, data analysis and data analytics is now ranging across the majority of industries, and opportunities should grow strongly.

Data analysts work in a wide range of industries and businesses. You might work in:

  • the corporate business arena, analysing sales trends or customer behaviours
  • the insurance and actuarial sectors, determining liability and trends
  • opinion poll analysis or analysing political polling data
  • in industry, predicting demand for goods or services
  • in government, universities or industry research bodies.


Data Analytics Career - Is It Right For You?
https://youtu.be/NOJKAzIH8hA

 

 

Organisation and Methods Analyst
  Information, Media and Telecommunications


Clerical or OrganisingHelping or advisingAnalytic or Scientific
Skill Level 5Skill Level 6

Organisation and Methods Analysts (or Business Analyst) study organisational structures, methods, systems and procedures. Organisation and Methods Analysts work closely with companies and organisations to help them change and improve the way they do things. They work in many industries from IT and financial services to telecommunications and retail. Future Growth Strong

ANZSCO ID: 224712
  
Alternative names: Business Analyst,
  
Specialisations: Change Management Facilitator, Industry Analyst, Quality Auditor, Skills Auditor
  
Knowledge, skills and attributes
   
To become a business analyst, you would need:

  • the ability to see problems from different angles and to solve them

  • excellent analytical skills

  • the ability to pay close attention to detail

  • excellent communication skills

  • excellent teamwork skills and the ability to work with people at all levels.



(Source: Your Career)

Duties and Tasks

As a business analyst, you would work with senior managers and other professionals to support changes to the way an organisation works. This could include changes across a whole business or may be limited to one part of it. For example, you might help to improve a company's decision-making processes, support the introduction of a new IT system or help to develop a marketing and sales strategy.

Depending on the particular project, you might typically:

  • Analyse and evaluate current systems and structures.

  • Discuss current systems with staff and observes systems at all levels of organisation.

  • Direct clients towards more efficient organisation and develops solutions to organisational problems.

  • Undertake and review work studies by analysing existing and proposed methods and procedures such as administrative and clerical procedures.

  • Record and analyse organisations' work flow charts, records, reports, manuals and job descriptions.

  • Prepare and recommend proposals to revise methods and procedures, alter work flows, redefine job functions and resolve organisational problems.

  • Assist in implementing approved recommendations, issues revised instructions and procedure manuals, and drafting other documentation.

  • Review operating procedures and advises of departures from procedures and standards.

  • Speak to managers about their development strategy to find out what they want the business to achieve

  • Carry out fact finding tasks into the business's processes to see what they do and how they do it

  • Analyse your findings and use data modelling methods to come up with recommendations for changes and improvements

  • Look at the potential impact and risks of your recommendations

  • Explain the benefits of your recommendations to the business

  • Keep a written record of requirements and recommendations, and how they were arrived at

  • Agree with the management team the best way to put recommended changes into place

  • Oversee testing and quality checks of recommendations

  • Support the staff who are responsible for making the changes and report any issues.


In some cases, you may also be responsible for managing the project all the way through to completion.

Organisation and Methods Analyst
(Source: Rome Business School)

Working conditions

You will usually work normal office hours, Monday to Friday. There may be some overtime necessary when project deadlines are close. Business analysts are usually office-based, although you may spend time travelling between sites if you work for a larger organisation.

You may work directly for a corporate, or for a consulting company that works in business process re-engineering or general consulting.


Tools and technologies

List of 5 Best Business Analysis Techniques (Source: WhizLabs)

SWOT Analysis

The term SWOT stands for its four elements –

Strengths,
Weaknesses,
Opportunities &
Threats

SWOT analysis is one of the most popular business analysis techniques followed in the industry. Furthermore, it is easy. It is an enterprise level analysis technique and not only limited to business analysis.
SWOT
MOST Analysis

The term MOST stands for its four elements –

M-Mission
O-Objective
S-Strategy
T-Tactics

MOST analysis is a powerful business analysis framework and among the best business analysis techniques using which the business analysts analyze what an organization does and plans to achieve the goal and what it should do to maintain strategic alignment. Hence, MOST analysis is a clear way to understand an organization on its ability and purpose.
MOST
Business Process Modelling


Business Process Modelling is all about process improvement. It is a legacy process, however, often used as a business analysis technique during the analysis phase of a project to understand or analyze the gaps between existing business process and future business process that business is opting for.
BPM
Use Case Modelling or UML
[Unified Modeling Language (UML)]

is a general-purpose, developmental, modeling language in the field of software engineering that is intended to provide a standard way to visualize the design of a system


Use case modelling is the technique to pictorially illustrate how the business functions should work in a proposed system through user interactions.
UML
PESTLE Analysis

There are always environmental factors which influence business in its strategic planning. These key factors are commonly known as PESTLE which stands for –

P- Political
E – Economic
S – Social
T – Technological
L- Legal
E – Environmental
PESTLE


Education and training/entrance requirements

You usually need a bachelor degree in information technology, information systems or business/commerce, business management, human resource management or another relevant field to work as an Organisation and Methods Analyst. Some workers have a Vocational Education and Training (VET) qualification.

To get into these courses you usually need to gain your senior secondary school certificate or equivalent. English and mathematics would be appropriate subjects to study prior to university.


Employment Opportunities

Employment of business analysts is projected to grow faster than the average for all occupations. Demand for consulting services is expected to grow as organisations seek ways to improve efficiency and control costs.

As markets become more competitive, firms will need to use resources more efficiently.

Growth will be particularly strong in smaller consulting companies that specialise in specific industries or types of business function, such as information technology or human resources. Government agencies will also seek the services of business analysts as they look for ways to reduce spending and improve efficiency.

 

Decision Support Analyst
  Information, Media and Telecommunications

Clerical or OrganisingAnalytic or ScientificSkill Level 5

Decision Support Analysts analyse and interpret information to identify options and advise their organisations on which ones to implement. Future Growth Strong

A Decision Support Analyst is a professional who conducts research, analyzes information and makes recommendations to businesses about their operations. These professionals usually work with various departments within a company to identify potential problems and find effective solutions. They present their recommendations to department or company leaders to help a business function more efficiently. For example, a decision support analyst may perform a cost-benefit analysis to help a company determine whether to build a new product based on operational expenses and projected sales.

DSS
(Source: The Australian Water Partnership)

ANZSCO ID: 263212

Alternative names: Business Intelligence Analyst (BI),
  
Knowledge, skills and attributes

To become a decision support analyst, you would need:

  • the ability to see problems from different angles and to solve them

  • excellent analytical skills

  • to be able to interpret large amounts of data

  • the ability to pay close attention to detail

  • excellent communication skills

  • excellent teamwork skills and the ability to work with people at all levels.

Decision Support Analyst
(Source: CareerHQ)


Duties and Tasks

As a decision support analyst, you would:

  • speak to stakeholders about their development strategy to find out what they want the business to achieve

  • carry out fact finding tasks into a business's processes to see what they do and how they do it

  • structure decision problems into algorithms

  • use data modelling and data analysis to come up with recommendations for changes and improvements

  • interpret data to solve tactical and strategic choice problems

  • look at the potential impact and risks of recommendations

  • explain the pros and cons of recommendation options to the business.


Working conditions

You would usually work normal office hours, Monday to Friday. There may be some overtime necessary when project deadlines are close. Part-time or flexible work arrangement should be possible.

You would usually office-based, although you may spend time travelling between sites if you work for a larger organisation. You may work directly for a corporate, or for a consulting company that works in business process re-engineering, data analytics or general consulting.


Education and training/entrance requirements

To become a decision support analyst you usually have to complete a degree in information technology, information systems, analytics, statistics or business/commerce. To get into these courses you usually need to gain your senior secondary school certificate or equivalent. English and mathematics would be appropriate subjects to study prior to university.


Employment Opportunities

Employment of decision support analysts is projected to grow faster than the average for all occupations.

Demand is expected to grow as organisations seek ways to improve efficiency and control costs. As markets become more competitive, companies will need to use resources more efficiently. Government agencies will also seek the services of decision support analysts as they look for ways to reduce spending, improve efficiency and conduct business more effectively.

 

Operations Research Analyst
  Information, Media and Telecommunications

Clerical or Organising
Analytic or ScientificSkill Level 5

Operations research analysts use computer software, and advanced mathematical and analytical methods, to help companies investigate complex issues, identify and solve problems, and make better business decisions. Operations Researcher develops methodologies for analysing and solving problems in government, business and industry, often using mathematical tools, statistical analysis and computers. Future Growth Strong

An Operations Research Analyst applies scientific method to problems concerning the management of systems of people, machines, materials and money in industry, business government and defence.
  
They conduct logical analysis of management problems in collaboration with management, with a view to understanding the system behind that problem, so that the system may be made to work in a manner that eliminates the problem.

ANZSCO ID: 224112
  

Alternative names: Operations Researcher,
  
Knowledge, skills and attributes

To become an operations research analyst, you would need:

  • excellent maths and IT skills

  • strong business acumen

  • a highly methodical and logical approach to your work

  • the ability to analyse and prioritise complex information

  • excellent written and verbal communication skills

  • strong problem solving and research skills

  • the ability to explain complex ideas clearly to non-experts.


Operations Research Analyst
Operations Research Analysts Career Video
https://youtu.be/IBWYsytaCbw

Duties and Tasks

As an operations research analyst, you might:

  • identify and solve real-world problems in areas such as business, logistics, healthcare, or other fields

  • collect and organise information from a variety of sources, such as computer databases, sales histories, and customer feedback

  • collaborate with workers familiar with a problem, or with others who have specialised knowledge of business processes

  • examine information to determine its relevance to a problem

  • use sophisticated software to run statistical analyses, simulations, predictive modelling, or other methods to analyse information

  • use the results of analysis to develop practical solutions to business problems

  • write reports explaining your findings, the impacts of various possible courses of action and your recommendations.


Working conditions

In a full-time role, you would usually work standard business hours, Monday to Friday.

Operations research analysts work inside companies, or for companies which specialise in business or strategy consulting for multiple clients. You would usually work in an office and spend time visiting other parts of the company, or client sites.

Operations Research Analyst
(Source: Zip Recruiter)

Tools and technologies

They develop methodologies for analysing and solving problems in government, business and industry, often using mathematical tools, statistical analysis and computers. Operations Research Analysts will perform many of their tasks on a computer. They will need to be familiar with project management software, and work processing and presentation software to prepare reports, human research ethics applications and presentations. Operations Research Analysts generally also need to be familiar with data management and statistical software, such as Excel and SPSS.
Most OR Analysts starts with a problem, which does not necessarily mean something has gone wrong or is about to go wrong. It could just be that a decision has to be made or that the person or group responsible for some activity believes it could be carried out better. From that point, there are a number of more or less standard steps to the conduct of the investigation. Some typical techniques used in OR include:

  • Network Analysis

  • Linear Programing

  • Stock Control Theory

  • Statistical Analysis


Education and training/entrance requirements

To become an operations research analyst, you would need to have a degree in an area such as mathematics, statistics, computing/IT, economics or business studies. Because operations research is based on quantitative analysis, you would need extensive coursework in mathematics or statistical / data analysis as part of your degree. To get into these courses you usually need to gain your senior secondary school certificate or equivalent. English, mathematics and physics would be appropriate subjects to study prior to university.

Continuing education is important for operations research analysts. Keeping up with advances in technology, software tools, and improved analytical methods is vital. For more senior roles, some employers prefer to hire applicants with a master’s degree, specifically in operations research or management science. A bachelor’s degree is usually sufficient for entry level roles.


Employment Opportunities

Employment of operations research analysts is projected to grow much faster than the average for all occupations. As technology advances and companies continue to seek efficiency and cost savings, demand for operations research analysis should continue to grow.

Many large firms have groups of OR Analysts (commonly 4 to 12 people). These are located in the steel, mining, oil, gas, chemicals, paper and engineering industries, and in airlines, railways, banking and insurance. Within the public sector, OR Analysts are also employed in health, education and electricity supply. Not all of these people have the formal title of Operations Research Analyst, and may be located in departments such as Industrial Engineering, Management Services or Corporate Research.

Some major Australian employers include:

CSIRO Quantas Ozminerals
KPMG ANZ BHP Billiton
Westpac Commonwealth Bank Dow
NAB Dairy Innovation Australia Orica
Woodside Petroleum AECOM Bayer
Xstrata    


Medical and Health Care Analyst
  Information, Media and Telecommunications

 

Clerical or OrganisingAnalytic or ScientificSkill Level 5

Healthcare analysts compile, organize, analyze, and interpret data related to healthcare, including patient treatment and healthcare products. A healthcare analyst is responsible for analyzing, compiling, and validating crucial medical data. They are tasked with compiling and maintaining data data needed by the company and will often offer insight as to how better improve care systems within their place of employment.

Most commonly, healthcare analysts work on the business side of medicine, improving patient care, or streamlining the way things are run.

They conduct research, implement data organization and analysis Future Growth Very Strong systems, and prepare reports and other documentation. They identify trends and gather industry insights, which may include competitive intelligence. They work closely in conjunction with other teams to develop strategies for using this data to gain a competitive advantage, improve operations, or better serve clients.

 

ANZSCO ID: 261111
  

Alternative names: Healthcare Analyst, Health Data Analyst, Public Health Analyst, Healthcare Business Analyst, Healthcare Information Management Analyst, Healthcare Consultant,
  

Knowledge, skills and attributes

Healthcare analysts typically have a bachelor’s degree and a background with roles involving the management and analysis of healthcare data. They must be proficient in the use of common data analysis tools and database platforms such as SQL Server and office programs like Excel. These roles require strong organizational and communication skills and problem-solving capabilities.

Healthcare analysts must have a thorough understanding of healthcare systems, data collection, and analysis, and they must have strong organizational and record keeping skills.

  • Bachelor's Degree in business, business administration, computer science or mathematics, or equivalent experience

  • Strict attention to detail and an eye for continuous improvement

  • Solid critical thinking and analytical abilities

  • Demonstrates excellent leadership and collaboration abilities, along with solid time management and problem solving skills

  • Strong command of English language, experience with writing protocols, and good communication skills

  • Comfortable working with statistics

  • Strong computing and scripting skills.


Healthcare Analyst
(Source: Career Foundry)

Duties and Tasks

Healthcare analysts are responsible for developing reports for upper-level management. They prepare monthly status reports, aid in corporate projects that deal with healthcare, compare medical budgeting to their prior analysis, and assist in customer service issues. They're also called upon for duties that include developing enhanced reports for their healthcare agency. All of these duties provide the healthcare agency with reliable information for their medical staff and patients.

  • Provide ad hoc and regular data analysis, metrics, and trending of investigations

  • Assure that the proper people receive problem reports as soon as detected

  • Present investigation metrics to Senior Leadership during quarterly compliance committee meetings and other settings as needed

  • Support external partnerships with outside counsel and audit firms as required

  • Operate effectively and efficiently within a complex, matrixed, and fast paced environment

  • Act as a liaison between hospital data sources used to compare performance

  • Design, develop, and configure interfaces and reports to support operational workflows

  • Deliver accurate and on-time deliverables, including reports, cost estimates, models, and ad-hoc analysis

  • Learn and perform all function of the integrated pest management program, including administration, scheduling, inspections, sampling, treatments, inventories, equipment maintenance, record keeping, report writing, and customer relations

  • Knowledgeable of the major business units of the company which relate to work responsibilities

  • Collaborate with the Executive [or upper management] and Communications team on the communications strategy and materials that elevate relevant research, policy developments, and approaches

  • Conduct performance analysis reports including trends, projections, external comparisons, and correlations.

  • Analyse and recommend opportunities and financial impacts of strategic partnerships,


Record keeping
(Source: University of Pittsburgh)

Working conditions

Healthcare analysts compile important medical data through the use of computer-based applications. They usually work full-time at health care agencies or hospitals to gather, compile, model, validate, and analyze data needed by the company. The data is then used to understand the current trends in the healthcare system and to make well-informed decisions.

Healthcare analysts may also be asked to develop initiatives for providing more effective healthcare, as well as resolve current service issues. They must have the ability to manage multiple projects, as well as meet time constraints and expectations. Designing new approaches to healthcare delivery may also be included within the position.

Tools and technologies

See tools described above "Data Analyst".


Education and training/entrance requirements

Healthcare analysts are usually required to possess a bachelor's degree in healthcare administration, mathematics, financing, business, or computer science. Healthcare analysts are usually required to have four to five years of work experience handling intricate database and information management responsibilities. Knowledge of PC-based applications used for data management is also required. A healthcare analyst must be good at multitasking and problem solving. A working knowledge of data analysis tools, such as SAS and database language tools like SQL, is very beneficial as well.


Did You Know?

But which data do healthcare data analysts work with?

Healthcare data analysts work with a wide variety of data; including those from electronic health records, clinical trials, devices, and patient surveys.

Clinical data
When people first hear about healthcare analytics, the first thing they often think of is directly improving medical outcomes. Medical records are a form of clinical data, which can be used to do this. Clinical data analysis is probably the oldest application of analytics in the medical industry. However, the level of insight we can now obtain from clinical data has increased vastly since the introduction of electronic health records (EHRs). Collectively, the big data we have access to offers unprecedented, real-time insights. For instance, it can be used to reduce the risk for patients, improve the overall quality of care, and even to train artificial intelligence to diagnose cancers.

Claims and costs data
Many healthcare analysts work for insurance providers or related organizations. Claims data generally refers to the information relating to patient claims and the subsequent medical interventions. Analyses of these data can be used in many ways. For instance, they might help medical institutions identify which medical areas to invest in, or to help insurers get a better grasp of their premiums. The data might also help identify areas where resources are being wasted or misused. The applications of claims data are very broad.

Pharmaceutical data
The pharmaceutical sector employs healthcare data analysts to support research and development, and to improve products and processes. For instance, several international pharmaceutical companies have an agreement in place to share historic cancer research data. They aim to accelerate the discovery and development of new cancer drugs. Pharma companies might also use data from genome sequencing or medical devices to target specific patients for clinical trials, ultimately improving the outcome of those trials (with more accurate data to use!)

Behavioural and sentiment data
Patient behaviour and sentiment analysis might not be the first thing you consider when thinking of healthcare analytics. However, these are an increasingly vital aspect of the industry. Today it is far easier (and far more acceptable) to track people’s retail habits, personal preferences, and feedback. For example, patient feedback on specific medical interventions can now be monitored in real-time. This means good behaviours or habits can be promoted, while common issues can be identified and dealt with quickly. For example, if patients suggest that they’re dissatisfied with a particular drug or medical treatment, this could inform an information campaign. Behavioural and sentiment data are also commonly used by private companies to market their medical products.
(Source: Career Foundry)

 

Big Data Engineer
   Information, Media and Telecommunications 

Clerical or OrganisingAnalytic or ScientificSkill Level 5Skill Level 6
Emerging Job

While big data is still data, it requires a different engineering approach and not just because of its size. Big data is tons of mixed, unstructured information that keeps piling up at high speed. That’s why traditional data transportation methods can’t efficiently manage the big data flow. Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data.

Big Data Engineers create and manage a company's data infrastructure and tools. They develop, construct, test and maintain architectures, such as databases and large-scale processing systems.Future Growth Very Strong

Big data engineers develop, test, and maintain Big Data solutions for a company. Their job is to gather large amounts of data from multiple sources and ensure that downstream users can access the data quickly and efficiently. Big data engineers communicate with business users and data scientists to understand the business objectives and translate those objectives into data-processing workflows. Essentially, big data engineers ensure the company’s data pipelines are scalable, secure, and able to serve multiple users.

Big Data Engineer
(Source: Career Foundry)

ANZSCO ID: 261111
  
Knowledge, skills and attributes

Big data engineers should have a strong knowledge of statistics, extensive programming experience, ideally in Python or Java, and the ability to design and implement solutions for big data challenges. Knowledge and experience in data mining, processing large amounts of raw data, and designing and maintaining relational databases for storage and data acquisition are desired. Experience with NoSQL is preferred.

  • Bachelor’s degree in computer engineering or computer science.

  • Highly developed analytical skills

  • Mathematics and statistical skills of the highest order

  • Strong organisational and project management skills

  • Work well as part of a team.

  • Experience with a broad range of big data tools, software and architectures:

    • In-depth knowledge of Hadoop, Spark, and similar frameworks.

    • Knowledge of scripting languages including Java, C++, Linux, Ruby, PHP, Python, and R.

    • Knowledge of NoSQL and RDBMS databases including Redis and MongoDB.

    • Familiarity with Mesos, AWS, and Docker tools.

  • Excellent project management skills.

  • Good communication skills - the ability to communicate technical concepts in non-technical language

  • Ability to solve complex networking, data, and software issues.

Big Data Engineer
(Source: Spiceworks)

Duties and Tasks

  • Meeting with managers to determine the company’s Big Data needs.

  • Developing Hadoop systems

  • Design, construct and maintain large-scale data processing systems

  • Store data in a data warehouse or data lake repository

  • Handle raw data using data processing transformations and algorithms to create predefined data structures.

  • Gathering and processing raw data and translating analyses

  • Evaluating new data sources for acquisition and integration

  • Designing and implementing relational databases for storage and processing

  • Working directly with the technology and engineering teams to integrate data processing and business objectives

  • Loading disparate data sets and conducting pre-processing services using Hive or Pig.

  • Finalizing the scope of the system and delivering Big Data solutions.

  • Managing the communications between the internal system and the survey vendor.

  • Collaborating with the software research and development teams.

  • Building cloud platforms for the development of company applications.

  • Maintaining production systems.

  • Training staff on data resource management.


Working conditions

You would usually work standard office hours, Monday to Friday.

You could work as an employee for a company that develops data analytics software, within a corporate environment, or as a consultant developing highly specialised, bespoke data mining infrastructure / architecture solutions for clients.

You would normally work in an office. You may also travel to meet clients and to attend conferences, industry and networking events.

Big Data Engineers at work
(Source: Maryville University)


Tools and technologies

See the listing of tools and technologies in Duties and Tasks; and, Knowledge, skills and attributes.


Education and training/entrance requirements

To become a big data engineer, you would need to complete a Bachelor's degree in computer science, mathematics, statistics or computer engineering.

To get into bachelor’s degree courses you usually need to gain your senior secondary school certificate or equivalent. English, mathematics, computing and coding subjects would be appropriate subjects to study prior to university.

Alongside the degree, a big data engineer needs to have a range of technical skills and knowledge to ensure that they can be successful in their role. So, from SQL, Python, and a variety of cloud platforms, the right knowledge can help an aspiring big data engineer succeed.


Employment Opportunities

Employment for big data engineers is projected to grow faster than the average for all jobs.

While data engineering is a relatively small occupation in Australia, it is growing strongly, both locally and internationally. There will continue to be increasing opportunities for employment, as companies across all industries look to use or better use big data and data mining to understand and reach their customer base.

Employers often require a bachelor’s degree in a related field and four to six years of experience. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. At the same time, they are facing a shortage of the necessary expertise. That’s why a data specialist with big data skills is one of the most sought-after IT candidates.

Most probably you need a big data engineer, if your business is in one of the following industries:

  • Internet of Things. IoT companies require fast data ingestion because they’ve got many devices sending in data non-stop. A big data engineer will carefully set up the data flow making sure no important information is lost.

  • Finance. Having all sorts of input data for processing, financial organizations have very specific
    big data needs that require a great deal of domain knowledge. It could be more efficient to train the existing staff on big data because they already know the systems.

  • Social. Making wise use of users’ data, social media companies understand who their customers are and what they like so that they can skillfully market products to them. Social media leverage the cutting edge technologies or even create their own big data solutions, e.g. Presto from Facebook and Apache Storm from Twitter.

  • Marketing and eCommerce. Tracking every online interaction of users with their site, marketing and eCommerce companies collect vast quantities of data about their customers.

    Also considering that this information is spread on hundreds of web servers’ log files and on many different systems, big data engineers have a lot of work to do here.

  • Government and Non-profits. All parts of government use big data and it comes in different flavors. Big data engineers will establish data processing where datasets will be joined together to process them at once for the most valuable insights.

 

Did You Know?

What is the difference between a big data engineer, a data analyst, and a data scientist?

While they share many data-related skills, each role nevertheless has a distinct function.


A big data engineer’s primary function is to manage and maintain big data infrastructures.

A data analyst’s primary function is to draw insights from data to inform decision-making.

A data scientist’s primary function is to construct the methods for extracting these insights from big data.
(Source: Career Foundry)

 

 

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