Data Science is a multidisciplinary field of study that combines advanced Mathematics, Statistical Analysis, Computer Science, Information Science, and Business Domain Knowledge. Data Science has existed for a long time; it used to be called ‘applied statistics’. But the capability to explore data patterns has quickly evolved in the twenty-first century with the advent of Big Data and the technologies that support it. In short, Data Science has found new ways to analyze and get value from Data. The core components of Data Science include Machine Learning, and Data Mining.
People who mine and develop predictive, machine learning, and prescriptive models and analytics from Big Data and deploy results for analysis by interested parties are called Data Scientists. They are known as Big Data Wrangler. As the capacity to collect and analyze large data sets has grown, Data Scientists have integrated methods from mathematics, statistics, computer science, signal processing, probability modeling, pattern recognition, machine learning, uncertainty modeling, and data visualization in order to gain insight and predict behaviors based on Big Data sets.
Data Engineering is involved in building the infrastructure and architecture for Data Generation. Data Engineering facilitates the development of the data process stack to accumulate, store, clean, and process data in real-time or in batches and make the data ready for further analysis.
Data Engineers create support systems for Data Scientists to focus on extracting meaningful insights from large datasets by leveraging scientific tools, methods, procedures, and algorithms.
David states, “Data Engineers are the plumbers building a data pipeline, while data scientists are the painters and storytellers, giving meaning to an otherwise static entity.”
| Data Scientist Skills | Data Engineer Skills |
| Programming | Programming |
| Data Wrangling | Cloud Computing |
| Data Visualization | Distributed Systems |
| Probability & Statistics | System Architecture |
| Multivariate Calculus & Linear Algebra | Database Design and Configuration |
| Machine Learning & Deep Learning | Interface and Sensor Configuration |
In short, both of the roles of Data Engineer and Data Scientist complement each other. Companies leverage Big Data must have professionals with both skill-sets i.e., Data Scientist as well as Data Engineer. Data Scientist rely on Data Engineer to build adequate pipelines for Data Generation and Analysis. Whereas Data Engineer prepare will be of no practical use without data scientists’ analytical operations.
