In this tutorial, we are going to discuss what are the main differences as well as similarities between data scientists and data analysts. We will also look into what a data scientist and data analyst do, their education and work experience, what are the required skills for both data analysts and data scientists, and a detailed comparison of their skills, work experience, salary, and education qualification.
Data scientists are the experts who will use their technical skills in order to solve problems that are very complex. They will also use algorithms, technical skills, and scientific methods in order to extract useful information or insights from both structured as well as unstructured data. Data scientists use data very carefully in order to make better and more suitable business decisions. Where a data analyst mainly deals with cleaning data, transforming data, generating inferences, and solving problems that means identifying the problem is not done by a data analyst they will only solve the existing problem. but a data scientist will first identify the problem then they will solve the problem. An important skill required for a data scientist is communication skills and it is not necessary for a data analyst.
A data analyst will collect data from different sources and organize the collected data. After organizing the data they will do the analysis.
One of the important roles, as well as responsibilities of a data analyst, mainly includes collaborating and engaging with salespeople and marketers who are there within the organization. This means data analysts should engage as well as collaborate with the different departments of a company. A data analyst should cooperate with peers who work in other departments.
The data model process of designing, and creating suitable algorithms and predictive models is mainly done by a data scientist. Hence each and every data scientists spend more time designing tools, finding out useful insights from the data, and identifying the business problems and data frameworks.
When we compare a data scientist with a data analyst they will always find out new tools or will develop new tools as well as methods in order to solve complex problems faced by a particular company in their business sector. They will always identify and solve business problems by extracting useful insights from the data with the help of predictive models. Identifying the problem is the very first thing done by a data scientist and after that gathering and data analysis is done in order to extract useful insights from the data.
Hence data scientists mainly identify the business problems, gather and analyze data, extract useful insights from data, communicate the findings with higher authority as well as with their colleagues, and design data model processes. They will use their technical knowledge, mathematical skills, and coding skills in order to solve as well as extract useful insights from data.
Educational requirements which are needed for a person to become a data analyst is a bachelor's degree mainly in the fields like statistics, mathematics, computer science or finance.
If one has a master's degree in data science, information technology, mathematics or statistics they can surely work as a data scientist.
Apart from this if one can earn a professional certificate from IBM or Google in data analytics and if you are skilled enough to acquire all the basic needs required for a data analyst you will be able to work as a data analyst for certain companies. A data analyst can become a data scientist if he/ she is ready to study more or ready to gain the required skills which are needed to become a data scientist.
Both should have great knowledge of mathematics. The data scientists should be experts in advanced statistics and predictive analytics whereas a data analyst should have great knowledge in foundational mathematics and statistics. Software and tools used by a data analyst are SAS, Excel, and business intelligence software.
Hadoop, MySQL, TensorFlow, and Spark are the tools used by data scientists. Analytical thinking and data visualizations are the other skills required for a data analyst. Machine learning, as well as data modelling, are the other skills required for a data scientist. Programming skills required for a data analyst are basic fluency in R, Python, and SQL. Advanced objectoriented programming is the main programming skill required for data scientists.
Data Scientist  Data Analyst 



Data Scientist  Data Analyst 


