ETL (extract, transform, load) is a process used to move data from one or more sources to a destination system, typically for the purpose of preparing the data for analysis or reporting. ETL involves three main steps:
· Extract: The first step in an ETL process is to extract the data from one or more sources. This may involve connecting to a database, reading files from a local or remote file system, or accessing data from a streaming platform such as Apache Kafka.
· Transform: The next step is to transform the data to fit the needs of the destination system. This may involve tasks such as filtering, aggregating, or reshaping the data, as well as applying data cleansing and data validation processes.
· Load: The final step in the ETL process is to load the transformed data into the destination system. This may involve writing the data to a database, writing it to a file system, or streaming it to another system.
ETL is often used in data pipelines to move data from various sources to a destination system for further analysis or reporting. The destination system may be a data warehouse, a big data processing platform, or another type of data storage or analysis system. ETL is typically used when the destination system has specific requirements for the data, such as a specific data format or schema, or when the data needs to be cleaned or transformed before it can be loaded into the destination system.
· Extract: The first step in an ETL process is to extract the data from one or more sources. This may involve connecting to a database, reading files from a local or remote file system, or accessing data from a streaming platform such as Apache Kafka.
· Transform: The next step is to transform the data to fit the needs of the destination system. This may involve tasks such as filtering, aggregating, or reshaping the data, as well as applying data cleansing and data validation processes.
· Load: The final step in the ETL process is to load the transformed data into the destination system. This may involve writing the data to a database, writing it to a file system, or streaming it to another system.
ETL is often used in data pipelines to move data from various sources to a destination system for further analysis or reporting. The destination system may be a data warehouse, a big data processing platform, or another type of data storage or analysis system. ETL is typically used when the destination system has specific requirements for the data, such as a specific data format or schema, or when the data needs to be cleaned or transformed before it can be loaded into the destination system.