Data Analyst Career Guide
Online shopping, social media engagement, Google ratings, website traffic, search trends — these are just a few of data sources that modern companies have come to rely on to inform their business models and interact with their consumer bases. Because of this, companies have now come to depend increasingly on their data analysts.
Data analytics in business can provide key insights to business owners that can guide informed decision making, giving businesses a competitive edge. But the importance of data analysis doesn’t stop at privately owned businesses. Even government agencies such as the U.S. Census Bureau rely on data analytics to study changes in our society and economy.
Due to the reliance of modern business on data, there are many fields of interest that aspiring data analysts can study and work in. If you are interested in becoming a data analyst, below is a comprehensive guide about job prospects, duties, educational requirements, and where to find opportunities in the field of data analytics.
Data Analyst Job Description and Duties
To understand the work of a data analyst, you first have to understand big data. Big data refers to data sets that are so large that they can’t be analyzed with standard statistical methods. There are two types of big data:
- Structured Data: refers to data that can be easily categorized, or show obvious patterns for analysis. Structured data is usually inherently numerical, and can include account transactions, GPS data sensors, and sales figures.
- Unstructured Data: refers to data that cannot be normalized, or categorized numerically. Unstructured data is usually language-based and includes customer reviews, photos, or social media posts.
Some big data work can be done automatically by software programmed by data scientists, but some cannot. This space is where data analysts work — particularly in the gathering and “cleaning” of big data.
Big data often comes from many sources, and in order to analyze it, data analysts must first collect all the data, and mine, or “cleaned” for missing, incomplete, or inconsistent data. Once data has been collected and cleaned, analysis can begin. Performing data analysis often means taking a question or unfulfilled need, and being able to transform the data in relation to that question or need into an answer. This requires a high level of critical thinking and an in-depth knowledge of your field.
Data Analyst Salary and Job Outlook
According to the Bureau of Labor Statistics (BLS), data and mathematical scientists can expect a higher-than-average rate of career growth over the next ten years. The average data scientist salary was reported by the BLS in 2019 at $100,560 per year, making careers in data science and research popular and lucrative.
There are multiple careers in the same vein as data analytics, including but not limited to:
- Data Scientists: similar to data analysts, data scientists collect and interpret data. Additionally, because data scientists typically need a masters degree, they are also involved in product design and development, and creating frameworks for new databases.
- Business Analyst: business analysts may work with data analysts to find improvements and innovations in all areas of a business, including products, services, manufacturing processes, and outreach. Business analysts may work closely with business systems analysts, who are often responsible for instituting and managing any proposed changes.
- Management Reporting: management reporting is a subset of data analysis that includes gathering business intelligence and performance data across different business processes. Management reporting can be carried out by a data analyst or data scientist.
- Corporate Strategy Analyst: corporate strategy analysts work with market research analysts to help business owners shape their long-term goals and make strategic decisions.
- Fraud Analyst: fraud analysts investigate counts of forgery or fraud on customer accounts, as a means of protection for both the business and the customer. Fraud analysts may work with data analysts to collect and interpret the origin of transactional data.
- Budget Analyst: budget analysts often work with project managers to create, maintain, and delegate an organization’s budget for internal projects, expansion, and other business expenses.
- Social Media Analyst: social media analysts work toward boosting the online presence and customer engagement of a given business. They may work with data analysts to gather and interpret engagement data — including likes, unique views, and comments — to create successful social media campaigns, as well as gauge interest.
- Market Research Analyst: Market research analysts use not just internal but external data to forecast market trends. They may work with data analysts to devise ways to collect and interpret unstructured data, such as surveys and polls.
Types of Companies That Hire Data Analysts
There are many companies working with big data that are looking to hire professionals in the field of data analytics. The most common of these organizations are:
- Start-ups: despite their small size, start-ups often hire data analysts to capitalize on growth opportunities that feedback and data collection can provide.
- Government Agencies: Because they serve a large populous, and often in more than one way, government agencies hire data analysts to mine through big data collections for the purpose of publishing reports or enacting systemic change.
- Companies that sell data collection/analysis services: Companies who sell data collection and analysis services obviously have a vested interest in not only being able to test and perfect data collection and analysis products, but to interpret their own feedback to continue to innovate.
- Large Corporations: Large corporations, especially with many branches across many states, need data and business analyst professionals because of the amount of data they have coming in coupled with the need to be able to interpret it both singularly, on a location-by-location basis, and within the larger, company-wide picture.
These are not the only companies that hire data analysts — every day, businesses are realizing the power that comes with harnessing their data properly. These types of companies have a pronounced need, and often offer internships and training programs as well.
Data Analyst Education Qualifications
Typical entry-level data analyst positions will require you to have a bachelor’s degree in the STEM field and a data analysis certification. You can become certified through your college or an independent accredited certification program. For higher-level positions, such as data scientists, you can pursue a master’s in analytics.
Data Analyst Skills
To have a successful career in data analysis, you will be expected to show proficiency in programming, coding, and machine learning algorithms and familiar with topics such as Artificial Intelligence (AI) and the Internet of Things (IoT). Below is a list of specific hard skills you may need to be a successful data analyst.
Required Hard Skills
The term “hard skills” means skills related to technical knowledge. For data science and analysis, many of the required hard skills have to do with the handling and storing of data, database languages, and the use of data analysis tools and programs. These skills include:
- Data visualization: presenting data via graphs or other visual tools;
- Data warehousing: central storage system for integrated data from one or more disparate sources;
- Database querying languages: code used to ask questions and maneuver databases;
- SQL: a domain-specific coding and querying language;
- Data mining, cleaning, and munging: the gathering and preparation of data before it is analyzed;
- Machine learning algorithms: automated algorithms that improve themselves through experience. This often includes AI and IoT applications;
- Google Analytics: a public data collection and visualization program;
- Tableau: a data visualization software solution that allows you to create dashboards and worksheets;
- Jupyter Notebook System: a data sharing and visualization software solution that allows you to share live code and algorithms;
- Github: a collaborative file-hosting software solution that allows data analyst teams to work within the same project;
- AWS S33: open-source relationship database that is cloud compatible;
- Python: high-level programming language;
- Extraction Transformation and Loading (ETL): procedure for copying data between different locations;
- Oracle: a database management system.
Resources to Learn Hard Skills
The skills required to be a successful data analyst may seem exhaustive, but there are events and opportunities any aspiring data analyst can attend to learn more. These resources might include clubs and meetups, Big Data Week, or networking with your student community or local businesses.
Many schools offer specialized certificates or training programs that you can pursue alongside your bachelor’s degree, which can help you practice important skills and build a portfolio as well. If you’ve already finished school, or are looking for something more flexible, you can check out some of the online courses that offer certification in coding, data science, advanced math, and other valuable skills:
Soft skills are related to your interpersonal skills. Soft skills are just as important to master as hard skills, as part of being a good worker is being good to work with. Some important soft skills for data analysts are:
- Strong and effective communication skills;
- Analytical thinking;
- Creative problem solving;
- Intellectual curiosity;
- Strong business sense;
- Attention to detail;
- Strong teamwork;
- Time management.
Finding a Data Analyst Internship
An internship can give you the on-the-job insider knowledge that fosters your success in a specialized, skill heavy field. An internship can also help you narrow down what field of data science you’d like to work with. Academic advisors, career counselors, and job boards can be a great resource when looking for internships, as can networking with your fellow students. In many cases, finding the right internship means knowing where and when to look.
Tips and Best Practices for Internships
Once you’ve found an internship, or several, that you want to apply to, it is important to know this: your first impression starts in your application, not at your interview. Job recruiters can see hundreds of applications in a day, so in order to put your best foot forward, you need to create a neat and individualized resume. Your resume should include:
- An introduction: in no more than a paragraph, you should discuss why you’re pursuing your field, or what interest you’re serving.
- Relevant extracurriculars: if you have none, omit this section. A good resume should always choose clarity over clutter.
- Relevant work experience: if you have none, talk about relevant classes you’ve taken and projects you’ve had to complete. If any of these projects exist online, link them.
- Personality: A strong resume should have some elements of intentional design. Showing off your personality makes you seem like a person, not just another page, and can help you be more memorable.
Once you’ve prepared your resume, do some research on the company you’re applying to intern with. Navigate their website with a notebook, and write down areas of interest, why you find them interesting, and any questions you may think of about their services or operation. These will be great talking points to include in a cover letter, or to cover in an interview, and will show your diligence and self-motivation.
How to Search For Data Analyst and Big Data Internships
Now that your application materials are prepared, it’s time to start applying. If you’re looking for an internship to double for academic credit, see if your university has an internship department or matching program.
You can also check local listings and company websites, but the most accessible place to find job listings is online job boards. Places like LinkedIn, Indeed, and Glassdoor are great resources, as you can find location-specific and nationwide job listings. These sites also let you set up alerts for keywords or companies, to help you stay on top of the job market in your desired field.
How to Search For Data Analyst and Big Data Jobs
Once you’ve completed your degree, internship, and any certifications, you’re ready to step into the industry. You can use the same application tactics and job portals to search for data analyst and big data jobs, but it behooves you to be more selective during the job application process.
There are a lot of considerations you need to make when applying for a job; can the salary support my lifestyle? What are the growth opportunities within the company? Do I agree with the goals and mission statement? This is where doing your research becomes vital, not just for supplementing your interview, but for ensuring that you’re applying to jobs that are the right fit for you.