What is Data Engineering?
Data Engineering comprises all engineering and operational tasks required to make data available for the end-user, whether for the purpose of analytics, model building, app development, etc.
Let’s see what is data engineering in easy words — Data Engineering is like take raw data doing multiple works to it and then giving clean dataset/database.
have you ever wondered, how is it possible that you search for a particular product on amazon and then you see it’s advertised on social media platforms? Actually it is possible using big data, like every activity of every smartphone users, different tech users are stored in a database and they see advertise and stuff related to their interest. But how is it possible to store this much big amount of data? It is possible using Big Data and it is made possible by Data Engineers.
SOME REAL WORLD BIG DATA EXAMPLES
- Discovering consumer shopping habits
- Personalized marketing
- Fuel optimization tools for the transportation industry
- Monitoring health conditions through data from wearables
- Live road mapping for autonomous vehicles
- Streamlined media streaming
- Predictive inventory ordering
- Personalized health plans for cancer patients
- Real-time data monitoring and cybersecurity protocols
The main role of Data Engineers revolves around storing data, data modelling, data warehousing, data lakes and running data pipelines.
Common activities of Data Engineer:
Data Engineer ingests data from various data sources.
Data Engineer builds and maintains data warehouses.
Data Engineer creates data pipelines.
Data Engineer creates an analytics table for a specific use case.
Data Engineer migrates data to various cloud services.
Data Engineer automates and schedules data pipelines.
Data Engineer deploys data quality issues.
Data Engineer designs and creates a database.
what are the daily basis responsibilities of Data Engineer?
Data Engineer Develops, constructs, tests and maintains architecture.
Data Engineer ensures data architecture will support and satisfies all the requirement of the business.
Data Engineer tries to discover opportunities for data acquisition.
Data Engineer develops new techniques for data modelling, mining, warehousing and production.
Data Engineer gives suggestions based on how to improve data reliability, efficiency and quality.
This was the first blog of my Data Engineering series, In the next part, I will be writing about Data Modelling.
THANK YOU!!
BE SAFE!!
