Data transformation and processing are fundamental aspects of data engineering, encompassing the conversion of raw data into valuable insights. In data engineering, this process involves a series of steps to clean, enrich, and structure data, making it suitable for analysis and consumption by downstream applications. By employing various techniques and tools, data engineers ensure that the data is accurate, consistent, and readily available for use. Whether it's performing ETL (Extract, Transform, Load) operations or implementing complex data pipelines, data engineering plays a critical role in unlocking the potential of data and empowering organizations to make informed decisions.
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