This is followed by mapping the schema to the target database, after which the actual loading can begin. This also includes the columns and data types that will be used to store the data. The schema creation process follows, which involves creating the structure of the database tables that will hold the data. A relational database management system, a data warehouse, or any other data storage solution can be used. This procedure consists of several steps, the first of which is determining the target source or destination. Here, the cleaned and transformed data is loaded onto the target source. The final stage or process in ETL is the loading phase. Additionally, we will review why ETL is needed, where it can be used, and the most popular tools used by individuals and corporation to carry out this process. In this article, we will explore ETL, especially what goes on at each stage of the process. ETL, in full, Extract, Transform, and Load, is a process through which this can be achieved. And the custodians of the majority of this data such as social media companies, and big tech corporations need to find efficient and effective ways to move these data from one point to another, without breaking the system. This goes to show the vast amount of data being generated by billions of internet users everyday. Statistics from 2023 says that about: 3.5 quintillion bytes of data is created per day, 5 billion Snapchat videos and photos are shared per day, 333.2 billion emails are sent per day, Skype has 3 billion minutes of calls per day Data and Information produced globally on a daily basis are growing at a very fast rate.
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