ETL specialists are an essential part of data science teams. They master the ETL process from the ground up by studying, analyzing, and understanding the situation of a company concerning data, they design and develop corresponding data storage systems.
With the pervading data obsession across all businesses, those who take control of their information will win the game. Accumulating information is only part of the job since data by itself is worthless unless it can bring practical value. What’s the practical value concerning data? It’s the opportunity to drive valuable insights and create a solid background for informed decisions.
Data engineering today becomes an inextricable part of business operations, and the specialists in this field are pushing the limits of new technologies to find new approaches to gathering, processing, and storing data.
Here, an ETL developer enters the scene. Whatever purpose you have while collecting data, you cannot use it in its initial format. Data processing includes taking information from storage and bringing it to a feasible format for further use. An ETL developer carries out this process by extracting, transforming, and loading data.
The article seeks the answers to the following
- What is ETL developer?
- What are their main duties?
- How to figure out when a company can benefit from such a specialist?
- Why are ETL professionals critical for modern enterprises?
What is ETL?
To start with, let’s focus on the very term ETL and discuss its constituents. What does the ETL abbreviation stand for?
- Extraction. Businesses collect data from abundant sources and store it in various formats. The source systems can include SQL servers, ERP, spreadsheets, data from vendors, and more. Extraction entails defining the data sources and gathering information.
- Transformation. Once the data has been collected from the sources, it must be validated before moving into the warehouse. The transformation stage includes the respective cleansing, mapping, and transformation of data.
- Loading. The ETL process finishes with loading the properly structured and formatted information into the target database. The type of database will depend on the required amount of data. Data warehouse, for instance, is used in big data management.
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