Sara C
Search Engine Optimisation and data science. Certainly, it almost goes without saying that each of these practices draws heavily on digital technology, computer engineering, and the internet, to be able to carry out their processes, methods and techniques. However, surely SEO and data science do not have all that much in common? On the contrary, when SEO and data science work together, they can achieve dramatic results – especially in terms of generating valuable digital insights for businesses.
So, for more information on how to learn about Search Engine Optimisation and data science, as well as career pathways in the field, and of course, how SEO and data science can work together to elicit positive results, just keep reading.
Learning about SEO and Data Science: Formal Education Pathways
So, what is data science, and how do you learn more about it? Well, if you’re interested in pursuing an in-depth education on the subject, it may be worth completing a tertiary qualification in the field, such as a Master of Data Science in Australia. As part of this type of postgraduate tertiary degree, students endeavouring to obtain a Master of Data Science qualification will learn and uncover key data science concepts which can be completed in four different stages. These stages are each made up of four different courses of study, which are as follows:
Stage A
The courses completed as part of Stage A of a Master of Data Science will usually include core units such as Applied Data Science Analytics, Data Visualisation and Communication, Data Wrangling, as well as how to apply practical data science knowledge and techniques using popular data analytics and computer programming system, Python.
Stage B
Stage B of this particular course involves the completion of the core study units which include Data Architecture, Ethics and Governance, Consumer Analytics, Financial Analytics for Managerial Decisions, and Data Analytics, Strategy and Change.
Stage C
The next stage of the course completion – Stage C – covers practical study units such as Machine Learning for Decision Makers, Leading in the Age of Digital Disruption, Shaping Organisations with Artificial Intelligence, and lastly, the completion of an Applied Data Science Strategy Consulting Project.
Stage D
Stage D is the final phase of the course, before graduation and obtaining your master’s qualification in data science. This last phase usually involves the completion of four study units which can be selected from a greater number of elective units. The elective units students must select from in Stage D of a Master in Data Science will usually include:
- Predictive and Prescriptive Analytics in Business
- Visualising and Communicating Insights in Business
- Digital Risk Management and Information Security
- Digital Innovation
- Business Project Management
- Business Analytics
What is Data Science, and How Does it Impact SEO?
If you’ve read this far, you’re likely still wondering – what exactly is data science? And, perhaps more importantly, how can data science knowledge, methodologies and techniques impact, affect and influence Search Engine Optimisation practice? Also, how can the two quite different areas of focus work together to achieve combined goals?
To answer the first question – what is data science? Essentially, data science is the practice of studying and analysing data to extract business insights. Using the processes of data science, massive ranges of data can be analysed at any one time. Data science draws from the principles of mathematics, artificial intelligence, statistics, and computer engineering for its data analytics processes.
So, what then, is SEO, and how does it relate to the practice of data science? Also commonly known as Search Engine Optimisation, SEO is the process of influencing search engine results for a favourable ranking of a specific website. Search Engine Optimisation or SEO achieves this goal through several different methods and techniques. These include on-page SEO methods such as producing keyword-optimised copy and content, as well as ensuring that the website in question meets the technical preferences of a search engine such as Google, for example. On the other hand, off-page SEO methods can involve backlinking and link building, where reference links to specific websites are placed on external sites to encourage and direct organic traffic to a certain page.
So, how do Search Engine Optimisation and Data Science work together, then? The most important element of this combined process is, of course, the application of technical SEO. Importantly, technical SEO techniques work best when combined with data science to influence algorithms and other programming languages.
Career Pathways in Data Science
If you’ve completed a tertiary qualification in data science, you will have many career options at your doorstep! These job prospects can include:
- Data Scientist
- Data Analyst
- Marketing Data Analyst
- Data Consultant
- Data Manager
- Data Engineer
Importantly, each of these data science career pathways is extremely highly regarded, and as such, you will be paid accordingly. A lucrative profession as a data engineer, for instance, can earn you an annual salary in Australia of approximately AUD 135,000 per annum. Even a lower-ranked data analyst can expect to earn an entry-level wage of up to AUD 90,000 annually. A mid-range data consultant or data manager can aspire to earn between AUD 115,000 and AUD 120,000 per annum. Certainly quite competitive salaries – especially in this financially strained day and age, where many individuals are struggling due to the current economic climate.
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We trust that this article has shed some light on the practices of Search Engine Optimisation and data science, and how they can impact and influence each other, as well as how these quite different practices can work together to elicit positive results. Most importantly, the aspects of technical SEO that can influence digital algorithms are just one aspect that can influence data science. So, if you’re interested in learning about this emerging area of study, obtaining a tertiary qualification in the field may be for you. If you do choose to pursue the route of completing a formal education qualification in data science, a lucrative and highly regarded career path could be yours.
