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Data Analytics explores the methods, processes, algorithms, and systems used to extract knowledge from data. Data Analysts are investigators, storytellers, and most importantly, problem solvers, who convert raw data into draw actionable insights.
As the backbone of any well-informed decision, data has become vital in driving the strategy and future roadmap of many businesses. The world’s big data industry has grown by 62% since 2018 and is currently worth an eye-watering US$274 billion.
As more industries become heavily data-reliant, new opportunities for data science roles have emerged including; Data Scientists, Data Analysts, Data Architects, Data Engineers, Statisticians, and Database Administrators.
A snapshot of the data analytics industry:
- Forbes has found that unstructured data is a problem for 95% of businesses
- More than 97% of companies are investing in improved data analytics capabilities
- The Australian data analytics market is projected to grow at a CAGR of 20% by 2025
- Over 16,000 Data Analyst roles are currently available in Australia
- The average salary for a Data Analyst in Australia is AU$102,889
How data analytics provides business value
With data becoming the new currency for business decisions and strategic roadmaps, some key benefits of data analytics include:- Helping businesses define decisions and goals: By dissecting previous performance, businesses can use data to prioritise their goals according to the highest importance and optimal results. Rather than making decisions based on gut, data can prove what has worked well within a business and define what future goals they should work towards.
- Adoption of best practices: Applying analytics to the design and control of processes enables businesses to optimise their activities to fulfil customer expectations and achieve operational excellence.
- Test informed decisions: Effective data collection enables businesses to stay competitive by testing and validating informed decisions and anticipating market demand.
- Reduce risk and fraud: Data Analysts are able to identify data patterns that can be used to make frameworks to detect fraud. These alerts help businesses track unusual activity and respond in an appropriate time frame.
- Deliver personalised experiences: By using data to tell stories, Data Analysts are able to empower sales and marketing teams to better understand their audience. With increased knowledge of buyer behaviour and motivations, organisations are then able to make personalised, well-informed solutions.
Key attributes of a Data Analyst
As a main driver of strategic business decisions, Data Analysts are in high industry demand and possess a wide range of skills. Here are some key attributes of a successful Data Analyst:
- Critical thinking: Before developing any hard skills such as programming, it is vital that a Data Analyst adopts a mindset of critical thinking. To ensure useful insights can be drawn, it is necessary that a Data Analyst has the ability to ask the right questions. The role of the analyst is to then uncover and synthesise connections within data, make sense of those connections and present their findings in an easily digestible manner.
- Understanding the data lifecycle: Data Analysts need to be comfortable with the acquisition, management and pre-processing of data, as well as mathematical and statistical analysis. Reporting and decision making is also extremely useful. Working through the full data lifecycle allows a Data Analyst to interpret data and present it in a meaningful way that can be used to support business decisions.
- Computer programming: Competency in programming languages such as R, Python, SQL, SAS, MATLAB and Excel are invaluable for Data Analysts, who use programming skills to extract, discern, and manipulate data. This information can then be presented into digestible visualisations in tools like Tableau.
- Data visualisation and presentation: Data visualisation and presentation are hand-in-hand skills for a Data Analyst. The ability to tell a compelling story with data and draw valuable insights is key to making any data useful.
- Machine learning: Machine learning and predictive modelling are fast developing fields that data science now relies on heavily. To develop these skills, a Data Analyst is required to have proficiency in programming languages in order to make predictions and automate existing data systems.
Data analytics aligns results in a quantifiable commercial outcome that is realistic and applicable to each situation. This takes a lot of patience and creativity.
Opportunities in the data analytics world
On a global scale, 2.5 quintillion bytes of data are created each year, with over 90% of all the data that exists today only created within the last two years. That’s a lot of data!
With the increasing demand for Data Analysts, there is a multitude of benefits of kickstarting a career in data including:
- Huge job opportunities: With data production only destined to grow, expect increasing demand for Data Analysts. For anyone keen to future-proof their career, there’s no chance that a data analytics skill-set will become obsolete, as long as it’s kept up-to-date to reflect industry innovations. Having data analytics capabilities is a great way to ride the next wave of digital change in the workforce.
- Increased earning potential: As with the basic economics of supply and demand, the growth of the big data market means that Data Analysts will continue to command high salaries.
- Expanding career development: Organisations of all sizes are beginning to prioritise data as an important part of their business operations. With new technology enabling increasingly sophisticated data analytics with large and diverse data sets, there are a multitude of roles and career pathways to choose from. Anyone entering or progressing in the field can pick from three types of data analytics to work with: prescriptive analytics, predictive analytics, and descriptive analytics.
- Data visualisation and presentation: Data visualisation and presentation are hand-in-hand skills for a Data Analyst. The ability to tell a compelling story with data and draw valuable insights is key to making any data useful.
- Ability to work with some of the world’s biggest brands: The world’s largest brands such as Apple, Amazon, and Uber are all looking into data to make well-informed decisions. For Apple, data is used to understand what additions and modifications customers need to deliver exceptional user experiences. For Amazon and Uber, predictive algorithms are used to map out recommended purchases and travel routes.
In the last 30 years, the rise of data, and how it is produced, consumed, and stored has dramatically revolutionised the way businesses make decisions. With the number of career opportunities set to increase, transitioning into a role in data presents an array of exciting pathways.
Learn how you can use data to make informed business decisions and present compelling stories with an Academy Xi Data Analytics course. Our Data Analytics courses come in two flexible online formats, so you can boost your skill-set and accelerate your career without putting the rest of life on hold.
To find out more and discuss your options, talk to a course advisor.
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