Within the data value chain, which activity focuses on transforming raw data-through cleaning, enrichment, and aggregation-so that it becomes trustworthy and ready for analysis?
The data processing (or preparation) stage of the value chain is where raw, often inconsistent data is transformed into a structured, high-quality form. Tasks such as data cleansing, deduplication, normalization, and aggregation occur here. These steps make the data reliable for subsequent analytics. While ingestion moves data into the platform, storage simply persists it, and visualization presents insights to users, only processing prepares the data itself for meaningful analysis.
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What is data processing in the context of the data value chain?
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What are some common techniques used in data cleansing during data processing?
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What activities are included in data processing/preparation?
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How does data processing differ from data ingestion?
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