What Qualifications Do You Need to Work in Data Analytics?



Data analytics involves interrogating information to find emerging patterns and trends. Uncovering hidden insight can help improve decision-making and drive meaningful change. Real world applications of data analysis include improving medical care, stopping hackers, enabling precision marketing, promoting smart energy usage, and helping the fight against climate change. 

If you are considering a career as a data analyst, you will need some proficiency in programming as well as an understanding of analytical models and theories. Transferable soft skills such as creativity, critical thinking and problem solving are important, and given that data analytics is applied across many different industries, sector specific knowledge is a big plus in any job application. You might have gained this from a summer job, internship, or work placement.

In terms of building your skills base, a degree in a related field such as mathematics, statistics or computer science is certainly useful, but not essential. So, if you have not been to university, or studied something different, there are plenty of other qualification routes to consider. Most are remote and self-paced, which means you can fit them in around your existing commitments. 

Software developers might be able to bypass qualifications altogether because moving into data analytics is a natural progression that builds on their technical knowledge and skills. But, for most people, a data analytics certification is usually the best way to go. 

Some of the most popular certifications include:

  • Google Data Analytics Professional Certificate
  • IBM Data Analytics Professional Certificate
  • Microsoft Certified: Power BI Data Analyst Associate
  • Amazon Web Services (AWS) Certified Data Analytics
  • SAS Statistical Business Analyst Professional Certificate
  • CompTIA Data Analytics Plus Certification

Although these qualifications are offered by different vendors and industry associations, they all share common themes which give you a good grounding in what you need to know as a data analyst.

Expect to cover the following:

  • Preparation and analysis - Understand which skills are required to solve different problems. Learn questioning techniques to uncover issues, as well as how to identify and collect the data you need using tools like Microsoft Excel.
  • Data mining - Data collection is a key part of the role. Learn how to mine data using tools like web scrapers, while being mindful of privacy issues at the same time. 
  • Exploratory data analysis (EDA) - EDA is an early-stage analysis that is particularly useful for hypothesizing solutions. Learn about the theory and how to apply to it.
  • Data visualisation and dashboards - This is key for exploring data and sharing insights. Data analytics certifications introduce you to different visualisation techniques and teach you how and when to use them. 
  • Database management - Creating, and managing databases is a fundamental part of data analytics. Understanding how to use SQL (structured query language), an industry-standard language for communicating with relational databases, is essential.
  • Programming skills - Data analysts need to know how to create and adjust algorithms. These certifications cover basic programming skills, usually in a language called Python. 

Unlike a degree, these data analytics qualifications can be achieved in months rather than years, so a career in this field could be closer than you think.


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