Big Data developers, analysts and scientists are titles that are becoming more frequently used these days within the workplace. These positions all deal with data, however, do you really understand the main differences between these roles? Data scientists aren’t exactly the type of scientists who wear lab coats and hold tests tubes over Bunsen burners. They are professionals who understand data from a business perspective. A data scientist’s skill-sets can be split into two different categories: data researchers and data developers.
What does Data Scientist need to know?
Data scientists require a solid knowledge platform of data modeling, computer applications, mathematics and statistical intelligence. With this level of expertise, data scientists are able to help businesses make accurate decisions through predictions. We can differentiate data scientists by understanding that they are more business-minded people who are able to communicate effectively with both business and IT decision-makers. We can also accept that they are skillful in analyzing the most relevant problems which will add the most value to the company once it is resolved. On the other hand, a Data analyst performs an array of duties including collecting, organizing data and then procuring statistical information from it. Once this phase of work is completed, they then proceed to visualize the information in such forms as graphs, charts and, tables. With these resources, data analysts will be able to build relational databases for a company. Like data scientists, we are able to split data analysts’ skill-sets, but into four categories. These are database administrators, data architects, operations and analytics engineers.
Developer/ Analyst/ Handlers of Big Data
- Analyzes the big data source, store and manage the data, finding trends and patterns
- Develops the technical infrastructure
- Forms data models to effectively find answers to business problems
What skills are needed?
The following skills are needed:
- High level of computer applications;
- Strong level of statistics and mathematics;
- Basic level of programming language (Linux/Unix);
- Basic level of databases;
- Programming in Java
- Knowledge with SQL.
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