Data Scientist vs. Data Analyst: What Are the Differences

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Data Scientist vs. Data Analyst

Data scientist or data analyst? What are the differences between them? Which one should you choose?

Well, those are common questions asked by people aspiring to become data experts. And I don’t blame them because these two fields are complementary and have several overlapping areas.

But at the same time, they have different roles, skill sets, and salaries that set them apart.

In this post, we will understand the difference between data scientists and data analysts. We will also see what skills they should have and what salary they earn. 

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    Data Scientist vs. Data Analyst: What’s the Main Difference

    These two fields have interconnected roles and are like two sides of the same coin. Data scientists ask the right questions, whereas data analysts find specific answers to those questions. 

    The role of data scientists is exploratory. They look for hidden patterns and develop models that predict future events. Whereas the role of data analysts is more descriptive, as they focus more on providing a description of what has already happened by looking at historical data.

    A data scientist’s work involves predictive modeling, deep learning, artificial intelligence, and working with massive datasets. They often deal with uncertainty and try to uncover new patterns or relationships in data. On the other hand, data analysts analyze data and generate reports that support decision-making. Their skills revolve around data visualization, querying, and basic statistical analysis.

    Both of them play a crucial part in helping businesses make data-driven decisions, but data scientists typically deal with more complexity and have a higher earning potential. We will see their salary in more detail, but let’s first understand what skill sets they need.

    Related: Data Engineer vs. Data Scientist

     

    Data Scientist vs. Data Analyst Skills

    Since they have different roles, they need different skill sets. Let’s understand this in detail:

    Data Scientist

    A data scientist may have to work with complex datasets, build predictive models using ML or statistical methods, use programming to develop algorithms, evaluate models, and provide actionable insights to business stakeholders. Here are the skills they usually need:

    • Data handling and dashboard creation with Adv. Excel
    • Firm grasp of SQL/MySQL database systems
    • Programming languages like Python or R
    • Big data tools like Hadoop and Spark
    • Advanced statistical methods for decision-making
    • Machine learning  and deep Learning 
    • Natural language processing and generative AI
    • Creative thinking and business understanding

    If you want to know more about topics you should study to become a data scientist, you can check out this data science syllabus. It’s followed by Ivy Professional School’s IIT-certified Data Science Certification Course. 

    Also, watch this video to understand the data science journey for freshers:

    Data Analyst

    A data analyst’s primary job is to analyze and visualize data to help businesses make informed decisions. They may collect and organize data, analyze it with statistical methods, identify trends, and generate reports and dashboards. Here are crucial skills they need:

    • Dashboarding and automation using Excel
    • SQL queries and relational database management
    • Data storage, retrieval, and application of ETL tools
    • Python, predictive modeling, and statistical techniques
    • Data visualization with Tableau and Power BI
    • Ability to analyze data in real-time
    • Ability to communicate the findings clearly

    You can watch this video to understand how data analysis is actually done to solve real-world problems. This is Mamta Mukherjee, an Ivy Pro student who has analyzed Netflix movies and TV shows using Excel to find valuable insights:

    Data Scientist vs. Data Analyst Salary

    Businesses need data to gather important insights, enhance business performance, and evolve in the market. So, both data scientists and data analysts are in high demand. But there is a difference in the salary they earn.

    Data Scientist

    The average data scientist’s salary is ₹12,00,000 per year in India. If you consider the cash bonus, commission, tips, etc., then the additional pay is ₹1,80,000 per year, which makes the average total salary of a data scientist ₹13,80,000 per year.

    It’s obvious experienced data scientists earn more salary. For instance, a senior data scientist with four years of experience may earn between ₹17 lakhs to ₹31 lakhs per year.

    The salary also depends on the company size. Bigger and established companies often pay more. For example, the salary of a data scientist at IBM is ₹8 lakhs to ₹20 lakhs per year, whereas in Amazon, the salary can vary between ₹9 lakhs to ₹25 lakhs per year.

    Data Analyst

    The average annual salary of a data analyst in India is ₹7,00,000. Considering the cash bonus, commission, and tips, the average total pay becomes ₹8,00,000 per year. 

    So, it’s clear data scientists usually earn slightly more than data analysts. However, the salary depends on various factors like experience, company size, industry, location, etc. If you are a senior data analyst with four years of experience, your average annual salary could be between ₹8 lakhs to ₹17 lakhs per year. 

    Also, there are companies like Accenture, Amazon, Cognizant Technology Solutions, Deloitte, Google, etc., who can pay you anything between ₹4 lakhs to ₹20 lakhs per year. 

    But what about the future? Well, the global data analytics market is projected to grow from $51.55 billion in 2023 to $279.31 billion by 2030, with a CAGR of 27.3%. So, you can expect increasing opportunities in the job market.

     

    Summing Up

    Now that you know the difference between data scientists and data analysts, you can make an informed decision about what you should become. 

    As I said, both data scientists and data analysts are in great demand. So, if you want to land your career in any one of them, you should get a certification from a reputed institution like Ivy Professional School.

    Ivy Pro is a top-ranking data science, analytics, and AI course provider in India with a legacy of 16+ years. The institute has several courses made in partnership with IIT Guwahati and IBM. 

    Also, Ivy Pro has trained over 29,500 learners and has helped them get jobs in Amazon, Cognizant, Deloitte, Accenture, IBM, etc. Visit this page to learn more about Ivy Pro’s courses.

    Prateek Agrawal

    Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.


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