How to Start a Career in Data Analytics

There’s never been a better time than now to start a career in data analytics. 

Data is everywhere; it comes in different sizes and from different sources. There’s data in each second of recorded security camera footage, every open-ended survey question response, and even in the quarterly grades of all the students in a given school district. Each day, an estimated 2.5 quintillion bytes of data are created. In 2020 alone, 1.7MB of data was made every second. However, until this data is sorted and analyzed, none of it is actionable. That’s where a Data Analyst comes in.

What Exactly Does a Data Analyst Do?

Data analysts use a set of techniques, tools, and processes to analyze raw data to extract relevant information, trends, and insights. This includes collecting data, organizing it, and storing it, then performing statistical analysis on the data. Once the information is collected, conclusions can be drawn from it, which can be used for problem-solving, business processing, decision-making, and predictions that can inform what a company’s next steps should be. In addition, most Data Analysts transform large sets of data into clear and engaging visualizations that are accessible to all members of a team or business. 

Data Analysts work in a variety of fields, from the healthcare industry to retail to Wall Street. Most Data Analysts have specialized training that allows them to thrive in the professional sector; Data Analysts tend to be detail-oriented and good with numbers. They are typically well-organized multi-taskers with strong presentation skills, which allows them to regularly share their analysis findings in a visually engaging manner.

Helpful Steps for Starting a Career in Data Analytics

For those who are considering starting a career in the field of data analytics, the great news is that there is no one “right” path, but rather many helpful steps that can be completed right out of high school, or decades later, depending on your professional goals and path toward reaching them. When deciding which path is best for you, there are several core skills and educational components that help Data Analysts to be competitive in the job market:

Education

Generally, those who aspire to work with big data receive formal education pertaining to this topic. There are three main avenues for studying data analytics: undergraduate study, graduate study, and certificate study:

• Undergraduate study. For many, pursuing a bachelor’s degree in data analytics or a related field is a great first step toward a career working with data. Receiving a bachelor’s degree in data analytics from a four-year institution is the most commonly selected option for aspiring Data Analysts. While not all colleges and universities offer a major in data analytics, many students choose to study a related field that teaches some related concepts and skills, such as computer science, math, statistics, or business. There are also several data-related undergraduate majors at colleges and universities around the U.S., such as a bachelor’s in Data Analytics, a bachelor’s in Data Science and Analytics, and a bachelor of science in Data Analytics, that provide relevant coursework and training.

• Graduate-level study. In addition to the bachelor’s degree in data analytics, a popular option for learners hoping to gain a more specialized and advanced set of skills is to pursue a master’s or doctorate degree in this field. Master’s degrees typically take between 12 and 15 months to complete. Although graduate study is rigorous and demanding, it provides many benefits for those interested in focusing their studies even further:
  • Because graduate study is more specialized than an undergraduate degree in data analytics, students often get to choose an area of focus in line with their career goals and electives that reinforce this trajectory. For example, some institutions offer graduate study in cybersecurity, financial analytics, or consulting. Master’s degrees teach dedicated learners how to directly apply the technical skills they learned in school to the real world. 
  • Many graduate programs teach programming skills in languages such as R and SQL, as well as data analytics programs like Tableau, which have direct applications for data-related work environments.
  • Earning a master’s or doctorate from a reputable program lets employers know that you have mastered more advanced skills than undergraduate education alone can provide, which may lead to a higher-level starting job or a promotion.

• Certificate in Data Analytics. Another great way to learn more about data analytics is to study for a certificate in this field. There are many perks to this form of learning. Most certificate programs are twelve months or less in duration. This makes certificate study a good option for those who don’t want to spend four or more years enrolled in college courses but still seek out industry-relevant training. In addition, certificate programs help learners specialize in one or several aspects of data analytics. For example, data analytics certificates sometimes focus on just one topic, such as R or Python programming languages, or provide a more robust overview of a topic, such as data visualization. Another benefit is that many certificate options in data analytics are currently being offered in the online format, which makes them a great option for learners who work, have family commitments, or may be traveling. 

Other Skills

In addition to education in data analytics or a related field, most Data Analysts also have other relevant skills as well:

• Real-world experience. In addition to a solid educational background, it’s also important for Data Analysts to be familiar with real-world examples of how data is being handled in various industries, such as government, business, and finance. This kind of knowledge helps paint a larger picture of the role data analytics plays within existing structures and indicates to employers that a candidate not only understands hypothetical analytic situations, but can also work under pressure.
• Technical know-how. Most employers seek out Data Analysts who bring a certain level of technical expertise to the table. While some jobs provide training to help employees learn programming languages or data visualization software, others search for candidates who already have this training. The following are some of the most important technical skills to brush up on if you are looking to start a career in data analytics:
  • Programming languages like SQL, R, and Python
  • Data preparation and cleansing techniques
  • Statistical analysis
  • Excel
• Creative skills. Great Data Analysts balance their technical training with the creativity required to bring their findings to life in a form that others can understand. This is why training in data analytics software and programs such as Tableau, Infogram, or Plotly is another important skill for aspiring Data Analysts. In addition to using these programs to help visually represent their findings, Data Analysts also must know how to present their findings clearly and engagingly, which often requires practice and feedback.
• A strong portfolio. No matter how you learn data analytics, it’s important to save your best work to showcase your skills in a portfolio. This selection of your work shows hiring managers that you have core skills relevant to the field, such as:
  • The ability to collect reliable data from various sources
  • The skills to clean and normalize this data
  • The creativity to transform complex information into visualizations that can be understood by a more general audience
  • The knowledge of how to pull important information from vast stores of raw data to provide actionable insights
• Soft skills. Hiring managers and recruiters value more than a college degree and Python training when searching for prospective candidates; they also want to hire someone who will be a contributing member to their corporate culture and compatible with their work environment. That’s why soft skills such as interpersonal communication, problem-solving, critical thinking, work ethic, and teamwork are also essential considerations for any well-rounded Data Analyst.
• An entry-level job in data analytics. Once you’ve achieved a desired level of education, assembled a portfolio of work, and have the creative and technical understanding of what it takes to be a Data Analyst, the next step is applying for entry-level jobs. It’s likely that most job listings won’t be a perfect match for your skills and training, but that’s okay. As long as you are a well-rounded candidate who can demonstrate to employers that you have some of the above-mentioned skills and background, you stand a good chance of being competitive for positions as a Data Analyst.

Learn More About Data Analytics with Hands-On Classes

Are you interested in learning more about data analytics? If so, Noble Desktop’s data analytics classes are a great starting point. Courses are currently available in topics such as Excel, Python, and data analytics, among others skills necessary for analyzing data. In addition, more than 180 live online data analytics courses are also available from top providers. Courses range from three hours to nine months and cost from $229 to $60,229.

Those who are committed to learning in an intensive educational environment may also consider enrolling in a data analytics or data science bootcamp. These rigorous courses are taught by industry experts and provide timely instruction on how to handle large sets of data. More than 100 bootcamp options are available for beginners, intermediate, and advanced students looking to master skills and topics like data analytics, data visualization, data science, and Python, among others.

For those searching for a data analytics class nearby, Noble’s data analytics Classes Near Me tool provides an easy way to locate and browse the 400 or so data analytics classes currently offered in the in-person and live online formats. Course lengths vary from three hours to 36 weeks and cost $119-$27,500.