In 2022, the world will produce 94 zettabytes of data. To put that into perspective, a single zettabyte equals 1 trillion gigabytes. Imagine 94 trillion GBs of data emerging daily.
No wonder “Data” is a big buzzword in business right now. And it is becoming increasingly important in all aspects of business. So there is a growing demand for people with data-related skills. But what does a career in data actually involve? In this blog post, we'll explore what data-related jobs are out there and what they entail.
Data encompasses everything from a company’s website to its inventory – and beyond. It’s a business’s complete database of consumer data, financial information, order history and employee records. But data professionals need to dig in many places, from social networks to apps to resources on the wider net.
The world needs professionals who know how to glean genuinely useful business insights from data. In an increasingly competitive digital world, data can drive changes that, even when small, bring significant competitive advantages. Lots of work goes into this – data professionals of all kinds need to take charge to build, manage, understand and protect data.
In this guide, we’ll be covering five popular data careers – and the skills career changers need to become a data professional.
A data analyst is responsible for collecting, cleaning, and analyzing data to help an organisation make better decisions. They use their skills in statistics and programming to find trends and insights in data.
A key part of a data analyst's job is to take data and turn it into insights that a company can use to drive impact. But that’s not all – they also ensure the data is accurate and of high quality. If you’re confident (though not necessarily an expert) with numbers and have an analytical mindset, you might be well-placed to succeed in this career.
Data architects are similar to real architects in that they are both creative visionaries who use maths and structure to bring their work to life. Data architects design, build and maintain the systems that all other data professionals rely on each day.
As a data architect, you’ll work closely with other professionals, including data analysts and scientists, to create the infrastructure – like databases – that they need to perform their jobs. What’s more, architects have to understand their clients’ needs, limitations, and challenges. Their solutions are often designed to work on a large scale with hundreds, if not thousands, of users.
Once their work is complete, the data architect maintains their system with ongoing maintenance and monitoring techniques. They optimize databases for stability and performance as well.
Data science is a broad field, so there is plenty of room for you to customise your career to align with your passions. Whether it’s healthcare or financing, data scientists are in-demand in almost every industry.
Data scientists use advanced tools and algorithms to glean the most powerful insights possible. For example, they often machine learning to process large amounts of data and draw informed conclusions. Machine learning allows computers to “learn” by following algorithms and instructions programmed by data scientists.
In simple words, machine learning is the use of artificial intelligence (AI) to make computer software improve its job on its own.
Every day looks a bit different for data scientists. In fact, it’s a great career if you are adaptable and are motivated by constant change and new problems to solve. Generally speaking, data scientists spend their workdays collecting, organising, shaping, and interpreting data for their organisations.
To work as a data scientist, you’ll likely need to know machine learning fundamentals, programming languages like Python, R, and SQL, and have a good grasp of statistics.
A data engineer makes sure data is collected and organized properly for analysis. They create storage solutions and data pipelines that make assessment and interpretation all the easier. As a data engineer, you would create databases and processing systems that data scientists use to perform their jobs.
Some skills a data engineer needs are programming, data analysis, and critical thinking. Data engineers are likely confident with at least a couple of programming languages (and often more). For example, they might have knowledge of Python, R, SQL or Scala.
A data engineer is a master problem-solver who loves using logic to develop solutions. They convert raw data into meaningful figures for their organizations, making it easier for data scientists and business leaders to gather insights and make new observations about their company and consumers.
While requirements vary by company, industry, and position, the core skills for all data professionals are:
● Programming. SQL is the bread and butter of any data professional – it’s a language that “talks to” databases. Other common languages include R, Python, Java and C++. A data bootcamp or online course can be a great way to learn these skills from scratch.
● Organisation. Anyone who works in data needs to love making sense of vast quantities of information. They need to thrive off structure, have a sharp eye for details, and enjoy setting and sticking to deadlines for all their projects.
● Communication. Working in data often involves communicating your findings to people with limited tech knowledge. You’ll need to be able to simplify complex, technical processes into easy-to-understand language, whether it’s in a face-to-face meeting or in a report.
● Motivation. Motivation keeps data professionals always improving their skills. This is an ideal field for anyone who wants to stay actively learning as long as they’re employed. Because technology changes so often, the data professional will need to always be educating themselves on best practices. Ready for the next step Data roles are not just an in-demand, they’re fulfilling and financially rewarding too. A specialist course or bootcamp can be a great way to get into data.
Data roles are not just an in-demand, they’re fulfilling and financially rewarding too. A specialist course or bootcamp can be a great way to get into data.