Data Pipelines

Data pipelines refer to the process of moving data from one system to another in a structured and automated way. In the context of data science and artificial intelligence, data pipelines are used to extract, transform, and load (ETL) data from various sources into a central repository, such as a data warehouse or data lake. Data pipelines can also be used to clean and preprocess data, as well as to perform feature engineering and model training. Data pipelines are typically composed of several stages, including data ingestion, data transformation, data validation, and data loading. Data pipelines can be built using a variety of tools and technologies, such as Apache Kafka, Apache Airflow, and Apache Spark. Data pipelines are essential for data-driven organizations that need to process large volumes of data quickly and efficiently.
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