Data analytics is a great entry-level path into the data landscape, but are there specific traits that you can recognize in yourself that will make you successful in this field? Michael Foote, a Career Coach at Springboard, believes that there are three qualities that make successful data analysts and shares them here! And if you recognize any of these traits in yourself, Michael tells you how to get started learning data analytics with Springboard Data Analytics 101.
Data analytics is a discipline focused on the collection, organization, storage, and analysis of data to extract insights. Data analytics also encompasses all of the tools and techniques used to accomplish these tasks.
The larger data landscape is vast and includes many different disciplines like infrastructure, machine learning, and artificial intelligence. However, data analytics is where all of this starts and it’s where businesses start to make valuable insights.
Data analytics is the logical first step in a data career. It doesn’t matter where you go with data, it all starts with data analytics. There are plenty of opportunities for growth within data analytics – you can go from entry-level to analytics managers, chief data officers, financial analysts, etc – but it’s also an excellent spot for people new to the field.
Students graduating from data analytics bootcamps with those core – SQL, Python, and data visualization – have a huge variety of options and many are able to leverage past experience to help them find a job. Data analytics is important in almost every field, so students can use the skills they learn in a bootcamp for a wide range of careers. Analysts fill roles in so many different fields, from marketing to healthcare to management. There is almost always an insight to be gleaned from data and if used responsibly, it can help solve major problems.
There aren’t any prerequisites to data analytics and I see people from a variety of backgrounds be successful in this program. Having a background in statistics or research doesn’t necessarily mean you’ll be successful in this field; in fact, sometimes the people you assume will be successful based on their backgrounds have the most trouble.
The students that are most successful in data analytics are motivated and eager to learn, and want to build a career for themselves.
If you’re the type of person that is determined to solve problems in your current job and are curious enough to get to the root cause of an issue, then you’ll likely enjoy data analytics. If you’re working at a company right now and asking yourself questions that you can’t answer without data, then that’s a great place to start. It’s important to enjoy cultivating knowledge since your whole career in data analytics will be based on learning new platforms, technologies, and tools.
For example, plenty of my students had functional backgrounds as project managers and coordinators. These students go into business analyst roles and act as liaisons to the tech team. And students who have been successful in marketing would make great marketing analysts with a data science skillset. Students with a strong background in sales would be able to land Sales Operations roles after a data analytics bootcamp.
One of my best students has been selling cars for seven years. He has dozens of interviews lined up. He’s curious, passionate, and excited about what he’s doing and that level of energy will allow you to be successful.
Some people are more analytical, naturally organized and attentive than others. These people usually pay more attention to the minute details in life and if you bring that skillset to data analytics, then you’re generally much more successful.
Some of my students have worked in healthcare as nurses or in healthcare management and now they’re coupling that experience with data analytics. These students are working as healthcare analysts and their understanding of how healthcare works is extremely valuable. Some of these students are landing salaries of $80,000-$100,000 right out of the gate.
Some people don’t mind math while others hate it with a passion. Math is an important part of data analytics and someone with a mathematically-oriented mind will be successful in building a career. However, it’s just as important to enjoy math since it will be one of the main parts of your job.
If you enjoyed your degree in finance or economics, but don’t want to work in a bank, then a job as a Financial Analyst with a data skill set would be really lucrative. If you have an MBA and want to upskill by learning data analytics and bring that to your current company, that’s something I see all the time.
The World Economic Forum published a report for 2022 that showed 85% of companies are going to adopt big data and data analytics technologies. There isn’t an industry in the world right now that isn’t looking at analytics and hiring analysts to make better business decisions.
We’re starting to look into predictive analytics, artificial intelligence, and machine learning. There are so many high-growth sectors that are going to leverage these skills. It’s a great place to invest time and effort into your education.
First and foremost, if you’re working in a company right now and you want to upskill, start looking for these responsibilities. Look for projects and other groups, it’s a great way to start applying knowledge and building a skillset.
Most of our students have done a little self-teaching for a while on GitHub and Youtube – these free platforms offer so much valuable information. Ask people in the industry, read articles, and do coding challenges. If this is something you're genuinely interested in, look for a short bootcamp to start moving the needle forward.
When you feel like you’re ready to commit and invest a considerable amount of time, look into an actual bootcamp. You will want that foundation, mentorship, and support, it’s easy to get distracted when you don’t have someone motivating you. There are plenty of free resources, but making the investment is absolutely worth it.
I tell students this is a huge growth sector and a great place to build a skillset, but you’re probably not going to get a six-figure salary immediately. It’s possible, but you have to be seriously invested in the career side as you learn the technical side.
What does the Data Analytics 101 Course cover at Springboard?
Data Analytics 101 is a four-week course and it requires no experience. It teaches the fundamental concepts and skills for a career in data analytics. Springboard pairs you with a mentor and you do hands-on projects and technical surveys. You also have opportunities to talk with a career coach like me.
This course gives them a good idea of what to expect further on so there are no unknowns for them in the bootcamp. We teach them how data science and data analytics work together and separately so they have a holistic understanding. We go over different problem-solving frameworks, structured thinking problems, Excel, and other technical topics.
Find out more and read Springboard reviews on Course Report. This article was produced by the Course Report team in partnership with Springboard.
Liz is the cofounder of Course Report, the most complete resource for students researching coding bootcamps. Her research has been cited in The New York Times, Wall Street Journal, TechCrunch, and more. She loves breakfast tacos and spending time getting to know bootcamp alumni and founders all over the world. Check out Liz & Course Report on Twitter, Quora, and YouTube!
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