Difference between Data Scientist and Data Engineer
What do they do?
- Data Engineers design, build, test, integrate, and optimize data collected from multiple sources.
- They use Big Data tools and technologies to construct free-flowing data pipelines that facilitate real-time analytics applications on complex data.
- Data Engineers also write complex queries to improve data accessibility.
- Data Scientists are more focused on finding answers to crucial business questions such as optimizing business operations, reducing costs, improving customer experience, etc.
- Using the data format offered by Data Engineers, Data Scientists ask relevant questions, find hidden patterns, hypothesis, and then reach fitting conclusions.
- Distributed systems
- System architecture
- Database design and configuration
- Interface and sensor configuration
- Cloud computing
- Data wrangling
- Database management
- Data visualization
- Probability & statistics
- Multivariate calculus & linear algebra
- Machine learning & deep learning
What tools they use
- Distributed systems
- Data pipelines tools (IBM infosphere DataStage, Talend, Pentaho, Apache Kafka, etc.)
- Big Data frameworks like Hive, Hadoop, Spark, etc.
- Advanced analytics and BI tools like Tableau Public, Rapidminer, KNIME, QlikView, and Splunk.
- ML libraries like Tensorflow, Theano, Pytorch, Apache Spark, DLib, Caffe, and Keras, etc.
What Salaries they get?
- According to PayScale, the average salary of Data Engineers in India is: INR 843, 140 LPA, whereas, in the US, it is US$ 92,260.
- The average salary of a Data Scientist in India is:
- INR 813,593 LPA, and in the US, it is US$ 96,089.
How to become one?
- Earn a bachelor’s degree and begin working on projects.
- Fine tune your analytics, computer engineering and big data skills
- Get your first entry-level engineering job/internship
- Consider pursuing additional professional engineering or big data certifications.
- Pursue higher education degrees in computer science, engineering, applied mathematics. Physics, or a related field.
- Pursue internship with any Data Science firm
- Take up data science online courses, and courses that teach Statistics, Probability, and Linear Algebra.
- Learn about basics of Natural Language Processing, Information Extraction, Computer Vision, Bioinformatics, and Speech Processing etc.
- Explore Optimization, Information Theory and Decision Theory.
- Obtain any professional data science certification
- Try managing databases, analyzing data, or designing the databases
Spread the knowledge