Data processing

Data processing is the systematic conversion of raw, unstructured data into high-quality, actionable intelligence for analysis and automated decision-making.

This is the engine for all modern analytics: We take raw data, clean it, validate it, and transform it into a usable format. The process follows a clear lifecycle: collection, preparation (cleaning, validation), input (e.g., via Apache Spark or batch jobs), processing (sorting, calculation), and output. Modern electronic data processing leverages advanced technologies like Python scripts for anomaly detection and machine learning (ML) algorithms for high-volume transformation. Effective processing is critical; for example, clean, well-structured data directly powers AI models, enabling businesses to automate workflows and unlock deeper insights across operations.

https://www.ibm.com/topics/data-processing