Data Analytics
What is Data Analytics?
Data analytics is the science of analyzing raw data to make conclusions about that information. The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. Data analytics help a business optimize its performance. (Source)
$274b
Global Market Size
(2023)
(2023)
$18.7b
VC funding into Data Analytics start-ups
3m
Data Analytics workers needed by 2028
$75k
Average annual salary of Data Analytics professionals
Data Analytics Pathways
Questions to Consider
- Are you naturally curious and inquisitive? Do you enjoy seeking out patterns and trends?
- Do you have an affinity for numbers and statistics?
- Would you be comfortable presenting your findings in a non-technical, understandable way?
- Are you interested in working alongside key stakeholders in a business and contributing to the overall business strategy?
Top Data Analytics Careers
- Business Intelligence Analyst: A business intelligence analyst’s most fundamental job is to find patterns — and value — in their company and industry data. BI Analysts will be expected to be comfortable analyzing data, working with SQL, and doing data visualization and modeling. (Source)
- Systems Analyst: Systems analysts use cost-benefit analysis to help match technological solutions to company needs. (Source)
- Machine Learning Engineer: A machine learning engineer, or ML engineer, is an IT professional that researches and designs artificial intelligence (AI) capable of self-operating to automate predictive analytics. The AI they create learns through its lifespan, hence the term ‘machine learning’ in the job title. (Source)
Top Data Analytics Companies
- Ernst & Young
- IBM
- Atlan
- Fractal Analytics
Related College Majors
- Applied Mathematics
- Data Science
- Statistics
- Economics
- Computer Science
Next Frontier Industry Roadmap:
Data Analytics
Want to start a career in Data Analytics but don't know where to begin? Start here!
- Do your research
Make sure you're well-versed in the basics. What is Data Analytics? What's driving it? Who are the innovators? What types of Data Analytics jobs exist? What are the major Data Analytics companies? If you're interested in a specific company, be sure to learn about its culture and values. This can make a huge difference in your job search!
2. Hone your "soft" skills
- Problem-solving: Problem-solving is at the very core of data analytics, so it’s essential that you enjoy tackling complex challenges. A key part of the role is knowing what data is required for a given problem and determining the most suitable method of analysis. If you don’t have the necessary data to hand, you’ll also need to figure out where and how to get hold of it—a problem-solving exercise in itself. If you relish the thought of solving all different kinds of challenges, you’ll find yourself quite at home in this role. (Source)
- Presentation and storytelling: The true mark of an accomplished data analyst is the ability to present complex insights in an accessible and user-friendly way. As the data expert, it’s your responsibility to make sure that key findings can be translated into action—and that means making them easily comprehensible for non-data experts. Do you have a knack for explaining tricky concepts in a clear and concise manner? Are you a confident presenter and an effective collaborator? These qualities will serve you well in the role of data analyst. (Source)
3. Learn the essentials
Most Data Analytics professionals have at least a Bachelor's degree, but there are several professional certifications that you can earn as well. Because there is such a growing need for data analytics professionals, many employers accept certifications and experience in lieu of a degree. You should also:
- Be proficient in MATLAB
- Excel in linear algebra and calculus
- Learn a statistical programming language, such as Python, SQL, or R
- Be familiar with data visualization tools, such as Tableau, Jupyter Notebook, and Excel
4. Build your portfolio
Be sure to include any projects that demonstrate your data analytics skills, including data aggregation, analysis, and visualization. These can either be projects you completed at school or personally! It's important to also demonstrate your specific aptitude for programming languages such as Python and understanding of SQL.
Also make sure your LinkedIn profile is up-to-date with your latest experiences and accomplishments and optimized using our Base 11 LinkedIn Optimization Guide.
Also make sure your LinkedIn profile is up-to-date with your latest experiences and accomplishments and optimized using our Base 11 LinkedIn Optimization Guide.
5. Gain hands-on experience
Data analysis bootcamps are a great way to get your foot in the door until you're ready to apply for your first internship. Be sure to search for opportunities in the specific industry you would like to work in, such as finance, retail, energy, public sector, etc.
6. Engage your community
Cultivate your network with a Base 11 community of like-minded individuals that you can connect with today using the community feature built right into this platform! We have a thriving community of students, early-career adults, and professionals on our discussion forums who can share insights, give advice, and help you on your STEM journey.
A Day in the Life of a
Data Analyst
Coming Soon: experience what a day in the life of a data analytics professional is like!
Additional Resources
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