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1 of a 2-part series.\u003C/b\u003E Once you've got the right data in, the next question is what to do with it. 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data\u003C/b\u003E\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EHow ingestion choices influence AI data freshness, reliability and operational cost\u003C/b\u003E\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EWhen Openflow managed connectors (database CDC or SaaS) are better than building your own pipeline\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EWhen not to ingest at all — querying in place and sharing instead of copying (zero-copy integrations) \u003Cb\u003Eto reduce unnecessary data movement and duplication\u003C/b\u003E\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch4\u003EWhat we’ll cover\u003C/h4\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003EThe ingestion patterns: batch → continuous → streaming\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EBatch and bulk loading for scheduled, high-volume data\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003EContinuous file 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