Data Scientist vs Data Engineer vs Data Analyst

Data is everywhere in the world. Data has been growing in very fast speed from last multiple decades specially from last 10 to 15 years. World has now massive amount of data due to all the major online platform like Social Networking Platform (Facebook, Instagram, Whatsup), Online Banking facility, Ecommerce (Amazon, Ebay, Alibaba, Flipkart), Web forms, Log files, Mobile Applications, Games and many more. We can say that the last two decades are “Digital Decades” which has converted world in to complete Digital World. We are continuously storing our data on various platforms like Online Bank Websites, Web Forms, Blogs, Social Networking Websites and many more. These bulks of stored data are very useful for every company. These companies use this data to understand the customer’s behavior and interest which will be helpful for them in various business operations like Customer Basket Suggestions, Product Recommendation, Disease Detection, Ads Placement, Customer Segmentation and many more. Every big company like Facebook, Amazon, Google etc is using this data for our business solutions and service improvement.

Data is available in various forms and scattered manner at various platforms. Operations like Data Collection, Data Cleaning, Data Usuage and Data Processing wants lots of time and man power. Every stage of data operation wants a unique data player who works on data and gets insights from this enormous data to solve the real business problem. Various posts are running in the world belong to data related jobs like Data Scientist, Data Engineer, Data Analyst, Big Data Analytic, Data Architect and many more. But the most popular and desired jobs are Data Scientist, Data Engineer and Data Analyst. But people are still confused between these three jobs because all are belong to data domain but there is a good difference between all three jobs and their roles, salaries, qualifications, tools etc.

Data Analyst: Data Analyst is a person who analyzes all type of data and makes it usable for management to take better business decision. He collects all type of data, analyze it and generate reports with charts, graphs and statistics, so the upper management understands it easily and make a good decision for their business.
Data Collection, Data Cleaning & Data Visualization
Database (Sql Server, My Sql)
Data Collection, Cleaning & Mining Tools (Microsoft Excel, Cassandra)
Data Visualization Tools (Tableau, Power BI)
Programming Language (Python, R)
BTech in Computer Science
Expected Salary: $ 65000/ Year

Data Engineer: Data Engineer is a person who solves the data problem with their scientific approach. They handle complete processing system to develop and maintain the architecture. They work on enormous amount of data to make pipeline architecture for business solution. They develop, test and maintain the architecture.
Creating & Integrating API, Data Pipeline, Build infrastructure for data generation
Database (Sql Server, Oracle)
Data Collection, Cleaning and Mining Tools (Rapidminer, Hadoop, Spark)
Data Visualization Tools (Tableau, Power BI)
Programming Language (Python, R and SAS)
B Tech in Computer Science
Expected Salary: $ 115000/ Year

Data Scientist: Data Scientist is a person who deals with structure and unstructured data to create systematic plan for a organization. They take the input from Data Engineer and Data Analayst and uses their advance skills to get insights from data and gives better solution for business problem. Data Scientist is the senior most member of the team.
Statistical Analysis, Build Machine & Deep Learning Models, Data Driven Problem Solving
Database (Sql Server, Oracle)
Data Collection, Cleaning and Mining Tools (Cassandra, Hadoop, Spark)
Data Visualization Tools (Tableau, Power BI)
Programming Language (Python, R, Java & SAS)
Technology (Machine Learning and Deep Learning)
Master’s in Computer Science, PhD in Data Science
Expected Salary: $ 140,000/ Year

Data Scientist, Data Engineer and Data Analayst jobs are their own roles in data business. Data Analyst works on beginning level of any business problem like Data Collection, Cleaning, and Visualization. Freshers can apply for this jobs. Data Analayst next promotion is Data Engineer after some years of experience. Data Engineer works on the intermediate level of any business problem like Creating API, Build Data Pipeline and Infrastructure. Data Engineer next promotion is Data Scientist after some years of experience. Data Scientist is the highest authority to solve any business problem. He works on the expert level of any business problem like handle structure and unstructured data, Use ML /DL algorithms to build model and most important find the solution of business problem which helps to make better decision system. Data Scientist mainly involve in company decision making system and we can say that management takes decision on the basis of Data Scientist business solution result and prediction. Knowledge of programming languages like Python and R are must. Student learn Data Science in two ways, First Data Science with Python and second Data Science with R. Python would be good because it is very easy to learn.

Entry Level Experience in Data Science Domain

Sometime it looks like that Data Engineer role is as equal to Data Scientist. They do all works which Data Scientist do to solve business problem. They build a system for Data Analyst and Data Scientist. But some companies want Data Scientist posts for their projects. We can say that Data Scientist is much more experienced then Data Engineer. But in some companies Data Engineer takes all the business solving responsibilities like Data Scientist. There is a pipeline structure in all three jobs like Data Analyst reports to Data Engineer, Data Engineer reports to Data Scientist and Data Scientist is the highest authority in data related domain who gives better business solution for any problem. All the major companies have produced many Data Science Jobs. Big companies like Google, Facebook, Amazon, Apple, Microsoft and many more have highly demand for Data Science Jobs. A study has said that Data Science will create millions of Data Science Jobs in next 5 years. So we can say that Data is very important for all major companies. Data Scientist, Data Engineer and Data Analayst are highly required to work on that data so they can fetch the best information from this data for any business solution.

Comparison Table

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2 thoughts on “Data Scientist vs Data Engineer vs Data Analyst

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