Data Analyst vs Data Scientist

Data-driven skills such as machine learning, artificial intelligence, and data analytics often enhance an individual’s employability in the modern business world. As the world relies increasingly on data on several aspects of business, research, and economy, the demand for data analysts and data scientists is high, with salaries typically above the national average. Employers are constantly looking for professionals versed in the knowledge of accumulating, calculating, and analyzing data. A well-designed data analytics programs develop the in-demand skills and knowledge required to analyze data and promote data-driven decision-making that supports business growth.

Businesses across the spectrum have distinct ways of defining a job role, but the reality is different. Job titles cannot always accurately reflect actual job responsibilities. The popularity of the job roles like data analyst and data scientist have often confused many individuals. For example, many people believe that data scientists are just an exaggerated version of data analysts. In this article, we will look into the difference between the two job roles.

Differences based on skills and education

Data Analyst and Data Scientist: Skills

Between the two, the most notable difference is in the skills possessed by the two professionals. The must-have skills for a data analyst include a good understanding of probability and statistics, versed with programming languages like SQL and Python, advanced MS Excel for analyzing data and creating reports using Tableau, data wrangling, etc.

On the contrary, a data scientist requires a strong foundation of linear algebra, calculus, statistics, and probability, versed with programming languages like SAS, R, Python, MATLAB, SQL, and Spart.

Data Analyst and Data Scientist: Education

One-year Diploma in Data Analytics is one of the most sought-after education paths by students aspiring to become data analysts. A data scientist typically holds a degree in data science, information technology, statistics, or mathematics. Other educational programs can help you become a data analyst or a data scientist. A formal course in a relevant subject can boost employability and promote career growth.

Moving forward, let’s learn about the job roles of a data analyst and a data scientist.

Who is a data analyst?

A data analyst is a trained professional whose primary role is to collect data from multiple sources organize it to perform data analytics through the data accumulated. Businesses generate data through customer information, transaction data, log files, etc. The data analyst has to transform the data into insightful and actionable information. They use several data manipulation techniques to analyze and interpret data sets that promote data-driven decision-making.

Who is a data scientist?

The amount of data being produced today is massive; hence IT geniuses have designed various tools that can efficiently handle vast amounts of data. Data scientists are professionals versed in using various tools and techniques to simplify data. They understand business challenges and opportunities to develop the best solution using the tools. Data scientists often use statistical methods, including data visualization and machine learning algorithms, to build predictive models to solve complex problems in data.

Data scientists play a vital role in any company because they communicate valuable information and insight to stakeholders and business leaders. Data analyst and data scientist are the two most in-demand job roles around the globe. Take the first step on your journey towards entering the field of data science with a diploma degree in data analytics. Apply Now!

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