Difference between Data Scientist and Software Engineer

1. Data Scientist :
Data Scientist is an expert analytical data specialist who has technical abilities to resolve complicated issues and additionally finds way to discover what issues truly need to be solved. And they are accountable for gathering data, examining it, and provide an explanation for large quantities of data to discover distinct approaches to assist and improve operations which makes gaining competitive aspect over rivals.

They explain what is going on by means of processing history of records and they additionally use range of superior machine learning algorithms to discover prevalence of an event in future which helps to make selections and predictions making use of this predictive causal analytics and prescriptive analytics to enhance commercial enterprise and operations. For this process, Data Scientist has to seem to be into information from many angles.

2. Software Engineer :
A software engineer is person who has expertise and applies disciplined, structured standards of software engineering to all stages – design, development, testing, maintenance, and assessment of software program that will keep away from low quality of software program product.



Difference between Data Scientist and Software Engineer :

S.No. Data Scientist Software Engineer
1. They analyze and manage large amounts of data that are coming from different areas by suggesting solution for them. They understand needs and requirements of their clients and deliver product without errors to end-users.
2. They follow similar approach to ETL process. The base for Software engineers for developing any software is SDLC or Software Development Lifecycle.
3. They follow Process Oriented approach to deal with data. They deal with Framework Oriented or methodology Oriented approach to make software products.
4. For dealing with data, they use various tools like Data visualization tools, Data Analysis tools and DB tools, etc. They use different tools in making software such as Testing Tools, Design Tools, Programming Languages Tools, Project Management tools, Web application Tools, etc.
5. Big data, Hadoop, Map Reduce, Apache spark, are main environment for them to analyze data. They need different environments and platforms for building software products such as Code development environment, Developing Programming, Testing & Maintenance environment.
6. They need to analyze data for processing tasks. They need to analyze user needs and requirements.
7. The sources of data for them including data from websites, data from Social Media, Transactions, Sensor Data, etc. Their sources of data including understanding and collecting data from their clients, User requirements, any new features developments.

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