In this article, we’ll explore the core differences between big data and data science and what each tech career pathway has to offer.
Updated on: 29 July 2021
Data is everywhere
Created in tremendous quantities, the current estimate for the amount of data created each day around the globe in 2021 stands at a massive 1.145 trillion megabytes. Much of that data will be sorted, categorised, analysed, and used to inform big decisions. Data is constantly changing the way we live, and will continue to do so in the future.
But, once deciding to build a career in data, which area should you put your precious time into? Big data or data science?
While the names of these two career paths might sound similar, they have vital differences that make each of them insightful and rewarding careers brimming with opportunity.
Trying to determine which career path is better suited to you? We're here to help. Let’s take a look at the difference between data science and big data to help you make your decision.
What are the differences between big data and data science?
Big data, as the name suggests, works with the enormous amounts of data, information, and statistics gathered by companies. Such vast volumes of information are unable to be processed and understood using traditional data analysis methods, so new developments have been made to comprehend and use this information.
Big data deals with three key types of data: unstructured, semi-structured, and structured. This covers a broad range of content such as information from social media, websites and images to XML and text files. Scientific methods are used to analyse and distil the information into a digestible format.
Data science also looks at the same three types of data but uses a different approach. Covering data cleansing, preparation, and analysis, data science uses a combination of skills including problem-solving, mathematics, programming and statistics.
Data science applies a scientific approach to interpreting the data using algorithms and machine learning to find disguised patterns among raw data. Data science intersects the data and computing sectors. To help distinguish the two fields further, data scientists work within an area of big data.
What are the differences between a big data and a data science career?
When it comes to discerning one from the other in relation to pursuing a career path, one is focussed on obtaining data to generate greater efficiencies and enhancing competitiveness, while the other is concentrated on modelling techniques that evaluate the big data.
Working in big data could lead to a career in finance, retail or communications. However, it’s all about working behind the scenes for these sectors, collating information that can change how businesses operate. Whether it’s using data to find a competitive advantage or identify untapped opportunities, big data is fundamental to the expansion, growth and development of businesses.
Data science, on the other hand, could lead to a career working across sectors including internet search engines, digital advertising or recommendation services. Data science takes information that big data has sourced and analyses it to make better business decisions. Data science careers are about delivering results through the application of learnings from big data.
What would be better suited to me?
Now that we’ve examined a few ways that data science and big data are applied to careers, you might be wondering how to decide which is best suited to you.
Check out our overviews below:
Do you want to focus on obtaining and sifting through vast amounts of data, using leading technology to discover a hidden gem that could propel a business into new territory? If so, then big data is most likely the career path for you. With average earnings coming in around AU$118,000 per year, it's certainly a healthy financial space to move to.
Big data is also a fantastic choice if you have a background in development or IT and are looking to change careers or upskill. Our big data collection can help nurture your skillset and develop you into an ultra-skilled big data professional. With Learning People, you can obtain qualifications from leading providers including Microsoft and Oracle and step into a rewarding career.
If you’d prefer to operationalise and scale data while taking on board compliance and governance, visualise the data and use it to inform better business decisions, then data science is the one for you. In our data science learner pathway, you can either upskill from a data analyst role or consider a career change altogether as we provide the training you need to make a difference.
Using programming languages including Python and R, you can integrate data with tools including Spark and Hadoop. With the potential to earn an average salary of AU$92,000 per year, there’s enormous opportunity in data science. Whether you want to work across the framework behind making digital marketing amazing through data-informed decisions, or deliver search queries through search engines in seconds, there’s a place for you in data science.
In this recent virtual seminar recording, we spoke to our past student Rory who studied with Learning People to switch careers from teaching to data science. Watch below to learn more about his experience with us:
Want to find out how you can transition careers, upskill or find a new pathway? Discover how you can make a difference in the world of data by getting in touch and speaking to one of our expert career consultants today.