If you are the type of person that can't wait to get your teeth into something, make sense of research, deep dive into a topic and put things in order, then maybe the role of a data analyst is something you've been thinking about.
The role of a data analyst can work across many different industries, from government agencies to medicine - anywhere you find data and research, you'll find data analysts.
All the research will have countless data and information; the data analyst's role is to make sense of that data. The data will go through several stages, which also go some way toward explaining some of the skills for an analyst too!
Most of the time for data analysts will be spent on building systems and compiling their findings into digestible forms for the company they work for. What makes this role so immersive is that a data analyst will be working on the project from start to finish.
They can be heavily involved from the ideation of the question - all the way through to the presentation of the data.
Data analysis is incredible at being able to spot patterns in data, and that is what makes them so valuable when it comes to creating solutions for current issues, and making predictions for the future.
Communication is a key trait of data analysis because they spend a lot of their time looking at data and making it make sense to others - simplifying the complicated.
Data analysis will collect and interpret data to produce a report or a solution for a specific issue faced by the client or business they work for.
The outline of the data analysis tasks is above, but there is a little more to it. While every day might not have each of the steps, data analysis will most often be somewhere in the process.
Gathering data can take many forms, and many analysts will collect data themselves. They might be tracking the location of website visitors, or they might be looking into something else. Data gathering is the foundation for the rest of the tasks.
The next step is cleaning the data. Cleaning the data looks at outliers, errors, duplications, and duplications. Cleaning the data removes all of these and puts the data into something usable. The data might be managed in a spreadsheet or go through a program, depending on the purpose of the data.
Modeling the data requires developing and designing a database's structural elements. You may decide which data types to save and gather, how to tie different data categories to one another, and how the data will actually look.
Interpreting the data means looking for a pattern and trends in the data so that you can begin to answer the original questions and look for a solution to what you are exploring.
Showing the results of your finding will typically be presented to stakeholders and those who can use the results to take action.
Although each of the companies that you work for will have its own requirements, there is some software that you will see across many different industries:
Before you launch into a role, you will learn how to use all of these software tools and more.
Knowing how to acquire, process, and analyze data has become an essential component of any company. Especially, as new technology rapidly increases the types and amount of information we can collect.
Data analysts are useful across many different industries like:
According to Glassdoor, the base salary for data analysis in the US in the region is $69,517. However, with some experience under your belt, you can quickly rise into senior role. Thus, getting a much higher pay rate.
Since data analysts are in high demand, there is much room for you to negotiate your pay. According to The World Economic Forum, data analysts are the number two growing industry.
Operations research analysts are liekly to have a 25% increase in employment in the next 8 years, market research analysts a 22% increase, and mathematicians and statisticians a 33% increase. That is much more than the 7.7% gain in overall employment.
If becoming a data analyst is something that you find interesting, here are some of the routes that you can use to break into the job role:
Not everyone has access to formal education. However, there are many options for self-study that will give you insight and practical experience. Access books on the subject - if you're on a budget, loan them from the library. Look for free courses and start building a portfolio.
Most job postings will require a degree or formal education, which shouldn't deter you from applying for your portfolio. If you are still in education, it is easier to get the right foundations by taking maths, computer science, and statistics.
There is a third route; professional certificate programs at the entry level often don't require any prior expertise in the subject. They can provide you with the opportunity to produce projects for your portfolio. Plus, you can receive real-time feedback on your work while learning fundamental skills like SQL or statistics.
One thing worth learning about data analytics - aside from having it as a career - is the deep insights into your business. You will be able to use data more efficiently, which makes a big difference to how you grow your business now and in the future.