The discipline of data analytics is one of the most important to today’s business world. Data Analysts, Business Intelligence Analysts and other pros trained in this area may develop and maintain databases, filter and analyze data, and prepare reports for stakeholders.

While there is some overlap between data analytics and data science, the two are in fact quite different. Data Scientists may use analytics in their roles, but the primary path for those who specialize in analysis leads to positions with titles like:

How the Field Can Define the Role

Unlike many areas of specialization, data analytics positions are often defined to a large degree by a sector, whether public or private. A large healthcare organization may need an Enrollment Data Analyst, a sports team hires a Sports Statistical Analyst, and a banking or finance entity may require a Fraud Data Analyst.

Depending on your goals, you might want to have both experience and knowledge of a particular field before you train for data analysis positions within it. If not, a comprehensive data analytics training program may be your best bet.

How to Decide

If you’re just getting started with data analytics, you may want answers to key questions like average salaries, responsibilities, and what sectors need Data Analysts the most.

According to Payscale, the average annual salary for a Data Analyst is around $63,000, while Salary.com lists it at around $80,000 per year. The discrepancy is attributable to the wide range of data analytics roles, but a fair estimate would fall between $45,000-$90,000 annually.

Salary is one of multiple factors to consider, and you may also want to know more about a specific data analytics role if you’re already working in a field and want to level up from a different position.

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Mastering Essential Tools

Data analytics professionals need a range of tools and resources to perform at a high level, and you can get training from multiple sources. Here are the primary ways to learn:

Online Resources

YouTube videos, articles, and webinars can only take you so far, and at some point you’ll need to choose avenues of direct training. Check out Noble Desktop’s Tech Blog for more information on data analytics roles, but consider one of the following formal methods for training in data analysis.

Individual Classes

A single class in a specific data analytics tool or programming language might be your best means of getting an introduction to data analysis. Some of these are required in numerous fields, but here are few of the most important.

  1. Python - One of the most popular languages in the world, Python is essential to Data Analysts, Data Scientists, Web Developers, and Machine Learning Engineers. If you have no Python experience, an individual class might benefit you.
  2. Tableau - An interactive data visualization tool, Tableau is a primary skill for many data analysis roles. Companies as diverse as LinkedIn, Verizon, and Charles Schwab use the Tableau analytics platform.
  3. Power BI - Microsoft’s Power BI for data visualization is a direct competitor with Tableau, but many data professionals are required to know both.

College or University Programs

While some schools offer data analytics degrees, many of these are Master’s in Data Analytics. Again, the broadness of the field precludes a one-size-fits-all approach. You might need a Bachelor’s in Computer Science or Business to qualify, depending on the program and where it should ultimately lead. Possible majors for undergraduate data analytics students include, but are not limited to:

  1. Data Science
  2. Computer Science
  3. Business
  4. Finance
  5. Math or Statistics

Bootcamps and Certificates

Of all the choices available to data analytics students, the bootcamp learning model is one of the most attractive. Longer than workshops but much shorter than degree programs, bootcamps and certificates offer intensive training measured in weeks or months, not days or years. Consider the following programs from Noble Desktop.

  1. Data Analytics Certificate - This program covers data analytics in detail, from Excel for Data Analytics and a Tableau Bootcamp to Python Data Science, SQL, and Machine Learning. Students should have a strong foundation in Excel before enrolling.
  2. Data Analytics Technologies Bootcamp - A targeted course for data analytics, this bootcamp covers Excel, SQL, and Tableau. Students are taken from beginner to advanced in all three in an immersive 57-hour program.
  3. Data Science Certificate - If you want to learn data science fundamentals, including popular data analytics tools like Python, Pandas, and SQL, consider this program. Like the Data Analytics Technologies Bootcamp, it’s also open to beginners.
  4. Python for Data Science Bootcamp - Another approach to this essential data analytics language, this course takes beginners through training in Python, Pandas, NumPy, and Matplotlib. Students can save by taking the bootcamp as part of the Data Analytics Certificate or Data Science Certificate programs.

Additional shorter courses relevant to data analytics include:

Professional Development & Certifications

Data Scientists often gain particular certifications while working in the field, and data analytics pros are no different. However, because so many Data Analysts work in business, finance, and other diverse fields, there may be other professional designations that do not overlap with data science.

Depending on the field where you ultimately use your data analytics training, the following certifications may be important to you:

  • CompTIA Data+ - A self-described “early career” certification for data analytics pros, this may be the first professional designation you earn in the field.
  • SAS Advanced Analytics Professional - The Statistical Analysis Software certification is especially important for big data professionals.
  • Associate Certified Analytics Professional (aCAP) - This data analytics certification is reserved for professionals who have completed a Master’s program.
  • Certified Analytics Professional (CAP) - Offered through the Institute for Operations Research and the Management Sciences (INFORMS), the CAP designation is considered “vendor- and technology-neutral.”
  • Microsoft Certified: Power BI Data Analyst Associate - Valued at many companies where Power BI is a requirement, this certification may be appropriate for a variety of data, business, and financial analytics professionals.

Additional Resources

Data analytics pros use a range of tools not well-known to those outside this rapidly-growing field. From data cleaning solutions like RingLead Cleanse and Clean Suite to automation tools like Darwin, analytics requires skills and technologies unheard-of a few short years ago.

You’ll need to research the field before you select a path, but opening one door doesn’t necessarily mean you’re closing another. As you research job boards and websites, graduate from a bootcamp or certificate program, and gain meaningful work in the field, consider the following organizations:

  • American Statistical Association (ASA)
  • Digital Analytics Association
  • International Institute of Business Analysis (IIBA)
  • The Data Science Association
  • International Institute for Analytics (IIA)

Whether you choose to work as a Data Analyst, a Business Analyst, or some other data science professional, proper planning and the right education and organizations can benefit you both now and over the course of your career.