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data ingestion

Contributor(s): Stan Gibilisco

Data ingestion is the process of obtaining and importing data for immediate use or storage in a database. To ingest something is to "take something in or absorb something." 

Data can be streamed in real time or ingested in batches. When data is ingested in real time, each data item is imported as it is emitted by the source. When data is ingested in batches, data items are imported in discrete chunks at periodic intervals of time. An effective data ingestion process begins by prioritizing data sources, validating individual files and routing data items to the correct destination.

When numerous big data sources exist in diverse formats (the sources may often number in the hundreds and the formats in the dozens), it can be challenging for businesses to ingest data at a reasonable speed and process it efficiently in order to maintain a competitive advantage. To that end, vendors offer software programs that are tailored to specific computing environments or software applications. When data ingestion is automated, the software used to carry out the process may also include data preparation features to structure and organize data so it can be analyzed on the fly or at a later time by business intelligence (BI) and business analytics (BA) programs. 

This was last updated in May 2016

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How can we measure the Data Ingestion Velocity? We would need to predict the future ingestion rate based on past history. What should be the factors we need to consider for measuring ingestion?
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From a technical communication/documentation standpoint, why are we using a biological term to describe a data processing concept? How is "ingestion" superior to existing IT terms, "import" and "process?" Ingestion just sounds like an unclear piece of jargon to me.
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