Difference Between Computer Scientist and Data Scientist

Computer Scientist: A computer scientist is a person who has complete knowledge of computer science that is the study of computation and application.computer scientists invent new technologies in the field, they often apply these to real problems, such as science or business. This may require them to work with other specialists, like engineers. Some of these scientists may specialize in a particular area, including programming or data science.

Data Scientist: A data scientist will be able to take data science projects from end to end. They can help to store a large amount of data, create predictive modeling processes, and present the findings. He organizes (big) data. Performs descriptive statistics and analysis to develop insights, build models, and solve a business need. The must-have skills for data scientists are Math and Statistics, Domain knowledge and Soft skills, Programming and Database, Communication and Visualization.

Computer-Scientist-vs-Data-Scientist
Below is a table of differences between Computer Scientist and Data Scientist:

Based on Computer Scientist Data Scientist
Definition A computer scientist is a person who has knowledge of computer science that is the study of computation and application A Data scientist will be able to take data science projects from end to end.They can help to store large amout of data, create predictive modelling processes and present the findings.
Skills Software development
Programming
Information systems management
Mathematics
Programming
Communication
Importance Computer scientist is very much necessary to understand the requirement and delivery the software product to end users without and vulnerabilities. Nowadays, loads of data are coming from multiple areas/fields. Hence as data grows, expertise needed to analyze, manage and make it a useful solution for business
Methodology For computer scientist, SDLC (Software Development Lifecycle) is the base which consists of requirements, software design, development, and software maintenance. Methodologies for Data Scientist are similar to ETL process.
Tools Design and Analysis Tools
Database Tools
Programming Languages Tools
Web application Tools
Data visualization tools
Data Analysis tools
Database tools.
Requirements Analyzing user requirement.
Designer.
Developer.
Build and Release Engineer.
Data Engineer.
Data scientist.
Business Analyst.
Data Analyst.
Data Engineer and also Data specialist.
Approach Approach for a Computer Scientist are:

  • Waterfall
  • Spiral
  • V&V model
  • Agile
  • Approach for Data Scientist are:

  • Algorithms implementation
  • Pattern recognition
  • Data visualization
  • Machine learning
  • Data Sources User requirements, New features developments and also demand for the some functionalities etc. Almost all website data can be considered for data source.Social Media, Business Apps, Transactions, Sensor Data, Machine Log Data etc.
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