Making Data Ingest and Pipelines Use Case-Driven – Gi

Making Data Ingest and Pipelines Use Case-Driven – Gigaom


Thursday, Feb 11, 2021
How can an organization ensure it has access to the best data, of the highest quality, with as little delay as possible? Getting there is a matter of policy, business priority, and technical architecture, as well.
Streaming data processing, classic Extract-Transform-Load (ETL), and change data capture (CDC)-based data replication each involve the ingestion, inspection, and movement of data. While typically used in different contexts and distinct platforms, it’s possible to “factor out” the differences, with corresponding benefits in tow. Technology stack precedent notwithstanding, organizations can look at all of these technologies through the wide-angle lens of processing data in real-time or in batch.

Related Keywords

Andrew Brust , Nir Livneh , Gigaom Research , Thought Leadership Webinars , Data Ingest , Pipelines Use , Cdc Tools , Change Data Capture , Data Ingestion , Data Integration , Dataops , Steaming Data Integration , ஆண்ட்ரூ மார்பளவு , சிந்தனை தலைமைத்துவம் வெபினார்கள் , குழாய்வழிகள் பயன்பாடு , ஸீடீக் கருவிகள் , மாற்றம் தகவல்கள் பிடிப்பு , தகவல்கள் ஒருங்கிணைப்பு , நீராவி தகவல்கள் ஒருங்கிணைப்பு ,

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