The hottest jobs in tech are mainly data scientists and data analysts. Many students are having a dream of grabbing these job opportunities at the beginning of their careers. Many people often confused with the term data scientist and data analyst, they consider these same. A person engaged in analyzing and infer multifaceted digital data, such as the practice statistics of a website mainly for assisting a business in taking decisions is called a data scientist. The person who is professional and has a focus of scrutiny and problem solving relates to data, types of data along with its relationships among data elements within a business system is called data analyst. Data scientist jobs are very much in demand these days. Here are the 18 differences between a data scientist and a data analyst.
| S.No. | Features | Data Scientist | Data Analyst |
| 1. | Definition | Data scientist are the one who gathers structured and unstructured data. | Data analyst is the one who collects, processes statistical analyses on the huge data set. |
| 2. | Job roles | There are different job roles like data researchers, developers, data creative and business people. | The different job roles like operations, data architects, database administrators. |
| 3. | Data visualization tools | Tableau | Google charts, Tableau, etc. |
| 4. | Data sources | Data scientist makes use of multiple data sources for gathering data | Data analyst focuses only on the data coming from CRM. |
| 5. | Data type | Unstructured and structured data | Structured data |
| 6. | Skills | A data scientist is familiar with all the skills that data analyst have along with a great foundation in modeling, mathematics, and statistics | Data analyst are the persons who have achieved mastery in SQL |
| 7. | Programming languages | Hive, Python, R, Scala, MATLAB, SQL, Pig. | Python, JavaScript, R, SQL, and HTML. |
| 8. | Responsibilities | Cleaning data
Massaging data Organizing data
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Analyze data
Mine data Identify patterns
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| 9. | Salary Package | Salary ranges between $95000 to $185000 | Salary ranges between $56043 to $170307 |
| 10. | Technical | They are more technical persons than data analysts. | They are a less technical person |
| 11. | Approach | They focus on taking decision belongs to the business | They focus on decision making |
| 12. | Communication skills | They possess great storytelling and management skills. | They don’t generally need |
| 13. T | Degrees | post-graduate degree | Undergraduate degree in Science, Technology, Education, and Mathematics |
| 14. | Preferences | Preference is given to a person who is Ph.D. along with a person from the STEM system background | Ph.D. is not mandatory but the STEM system would be there. |
| 15. | Experience | Experienced in scrutinizing data from Google Analytics, AdWords, Facebook Insights, etc.
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Experienced in functioning with the agile methodology. |
| 16. | Backend software | SQL and NO SQL for structured and unstructured data. | SQL for structured data only. |
| 17. | Preferrable software | Experienced in working with distributed systems. | Experienced in Microsoft Office and excel. |
| 18. | Algorithms | ML algorithms are used to suit customer needs. | Customer-centric algorithm models are preferred according to customer requirements. |
In this blog, we have tried to tell the main 18 differences between a data scientist and a data analyst. This blog gives you a wider picture of different career options. Feel free to ask me related queries in the comment section
