Data engineering is the process of preparing, storing and visualisation data for operational and analytical purposes. It is considered one of the key aspects of data science and focuses primarily on actual applications of data analysis and data collection. Data engineering involves pulling and gathering analytical data from various sources through data pipelines. The gathered data then needs to be processed, consolidated, structured and made ready for analytical use. The functions of data engineering are performed by experts in the field known as data engineers.
Points to Remember
- Data engineering is an equally important field as data science. In fact, data scientists depend on data engineering for their data. Without properly structured data and information, data scientists may not be able to obtain the desired results.
- Data engineering generally demands that data engineers have multiple skillets. A data engineering may have expertise in big data technologies and several types of data processing and data ingestion frameworks and tools.