Data Science vs. Data Analytics – What’s the Difference? What Is The Salary Difference?

Data Science vs. Data Analytics – What’s the Difference: Both data science and data analytics are commonly used terms – but are they the same? What is the difference between the two?

Data Science Vs. Data Analytics – What’s The Difference

What Is Data Science?

Data Science is a multidisciplinary field that uses algorithms, predictive models, and machine learning to solve complex problems. It involves gathering, cleaning, and analyzing large datasets to extract meaningful insights. A Data Scientist not only analyses past trends but also predicts future outcomes, helping companies make proactive decisions.

“Data is the new oil, and Data Science is the refinery process,” says Sundar Pichai, CEO of Alphabet.

4 Key skills of a Data Scientist:

• Programming in Python or R

• Machine learning and artificial intelligence

• Data wrangling and visualization tools (like Jupyter Notebooks)

• Statistical modeling

What Is Data Analytics?

Data Analytics, on the other hand, focuses on interpreting existing data to find actionable patterns. It is more about answering specific questions like “Why did sales drop last quarter?” or “What trends are impacting customer behavior?”

A Data Analyst works with tools like Excel, Tableau, and SQL to generate reports and dashboards for business intelligence.

4 Key skills of a Data Analyst:

• Proficiency in Excel, SQL, and Power BI

• Data visualization skills (e.g., Tableau)

• Reporting and business intelligence tools

• Statistical analysis

What Is The Difference?

This table highlights the core differences. So, “what is the difference between data science and data analytics jobs?” Data Science jobs demand advanced programming and machine learning expertise, while Data Analytics roles require proficiency in visualisation tools and statistical analysis.

Which Is Better: Data Science or Data Analytics?

The answer depends on your interests and career goals. If you love coding, solving complex problems, and predictive modeling, Data Science might be your ideal choice. However, if you enjoy interpreting trends and working with visualisation tools, Data Analytics could be the better fit.

“The goal is to turn data into information, and information into insight,” as Carly Fiorina, former CEO of HP, puts it.

• If you enjoy coding and want to explore advanced AI and machine learning techniques, data science might be your path.

• If you prefer working with structured data to solve immediate business problems, data analytics is a great choice.

What Is the Salary Difference Between Data Science and Data Analytics?

Now, let’s talk numbers—one of the most important factors in career decisions. According to industry reports:

• Data Scientist: In India, entry-level salaries start around ₹6–8 LPA, while experienced professionals can earn upwards of ₹20 LPA.

• Data Analyst: Entry-level salaries range between ₹3–5 LPA, with senior roles fetching ₹8–12 LPA.

“The salary reflects the scope of work,” says Girija Shankar, Placement Head at ZELL. “Data science demands a more advanced skill set, hence the higher pay.”

Clearly, Data Science roles are more lucrative due to their complexity and demand for advanced skills. However, both careers are rewarding and offer tremendous growth potential.

Which Is More in Demand: Data Scientist or Data Analyst?

As of 2024, both roles are highly sought after. However, the demand for Data Scientists has surged with advancements in AI, machine learning, and big data. Still, Data Analysts remain crucial for organisations to make data-driven decisions efficiently.

According to LinkedIn’s 2023 report, data scientist roles grew by 40% in India, while demand for data analysts surged by 35%.

Pro ZELL Tip: Upskilling in either field with real-world projects is the fastest way to succeed.

How Can ZELL Help You Choose the Right Career Path?

At Ze Learning Labb (ZELL), we offer courses tailored to help you excel in both fields. Whether you want to become a data scientist or a data analyst, our programs provide hands-on training with real-world projects. Plus, with our placement support, we ensure you’re job-ready!

Why Choose Ze Learning Labb?

•           Expert trainers with industry experience

•           Flexible learning schedules

•           Financial assistance for eligible students

•           Partnerships with top MNCs

On A Final Note…

So, “Data Science vs. Data Analytics – what’s the difference?” boils down to skills, interests, and career goals. Data science focuses on predicting the future, while data analytics analyses the present. Both fields are lucrative, but the choice ultimately depends on your aspirations.

Take the first step today! Enrol in Ze Learning Labb’s Data Science and Data Analytics programs to build a promising career in the data industry.

Still confused? Drop your questions in the comments below, and we’ll help you make the right decision!

For more details, explore ZELL’s Data Science and Data Analytics courses!