Using data engineering, you can explore, visualize, clean, and prepare your data. The data engineering process is a common first step for many spatial analysis and mapping workflows. The Data Engineering view and ribbon can help you better understand your data and prepare it for GIS workflows.

Data engineering involves designing, building, and maintaining the infrastructure that supports data generation, storage, and processing. It focuses on creating robust pipelines to extract, transform, and load (ETL) data from various sources into data warehouses or data lakes for analysis and decision-making.
In Geographic Information Systems (GIS), data engineering entails managing and processing spatial data. This involves tasks like collecting, cleaning, integrating, and analyzing geographic data to produce meaningful insights and visualizations. It also involves developing and maintaining the infrastructure for storing and accessing spatial data efficiently.
Data engineering plays a crucial role in unlocking the full potential of GIS by ensuring the quality, reliability, and usability of spatial data for various applications ranging from urban planning and environmental management to disaster response and business intelligence.

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