In today’s data-driven economy, data analyst vs. data scientist is a comparison that frequently comes up among students and professionals exploring tech careers. Data scientists and data analysts are two of the most in-demand and high-paying professions. According to the World Economic Forum’s Future of Jobs Report 2020, data analysts and data scientists lead the list of fastest-growing job categories across industries.

While both are data-oriented professions, understanding the data analyst vs. data scientist distinction is key for choosing the right career path.

Understanding the Roles: Data Analysts vs. Data Scientists

The most significant difference between a data analyst and a data scientist is the manner in which they deal with data.

What Does a Data Analyst Do?

Data analysts deal with structured data and apply it to solve precise business problems. They depend on tools such as SQL, Python, R, and data visualization tools. Their work often include:

• Collaborating with business leaders to identify data requirements
• Gathering data from internal and external sources
• Cleaning and data preparation for analysis
• Finding trends, correlations, and actionable insights
• Presenting findings in the form of visual reports and dashboards

What Does a Data Scientist Do?

Data scientists, however, extend beyond the analysis by forecasting future outcomes using more advanced methodologies. They handle both structured and unstructured data and, in many cases, develop machine learning models and AI solutions. Their work typically includes:

• Collecting and processing large amounts of raw data
• Develop predictive models and specialized ML algorithms
• Developing tools for measuring and guaranteeing data quality
• Developing dashboards and sophisticated visualization tools
• Implementing data workflows through programming

In most aspects, a data scientist role is an extension of what was developed by data analysts, hence a more sophisticated step along the data career ladder.

Data Analyst vs. Data Scientist: Qualifications You’ll Need

For Data Analysts

Most junior analyst roles call for a bachelor’s degree in computer science, statistics, mathematics, or economics. Some also desire certifications for tools such as Excel, Power BI, or Tableau.

For Data Scientists

A bachelor’s degree in data science is a minimum, but most professionals also opt for master’s degrees in specialized topics such as:

• Machine Learning
• Cloud Computing
• Cybersecurity
• Advanced Statistics
• Networking and Data Engineering

If you’re new to this, it’s a good idea to start out as a data analyst. This gives you those critical skills and lays the foundation for moving into more intricate data science positions later on.

Skills Comparison: Data Analyst vs. Data Scientist

Both professions have core skills in data analysis, but data scientists tend to build on those with advanced methods. Here’s a quick side-by-side breakdown of the skills involved in the data analyst vs. data scientist debate:

Launch Your Career with J2K AI Systems & Technologies

Whether you are interested in extracting business insights or creating smart models, it starts with solid analytical prowess. At J2K AI Systems & Technologies, we provide starting and advanced level courses to prepare students from any background to succeed in the data space.

Begin your journey today with our Data Analytics Fundamentals or AI and Machine Learning Essentials course. Enhance your resume, get certified, and gain future-proof job prospects in a matter of months!