Data is huge and growing, with commercial open source everywhere in the stack
Extracted slide text
Data is huge and growing, with commercial open source everywhere in the stack
Data is huge and growing, with COSS omnipresent in data infrastructures. Stack map across data sources (OLTP DBs via CDC, applications/ERPs, event collectors, logs, third-party APIs, file and object storage), ingestion and transformation (connectors: Fivetran, Airbyte - we are here; data modeling: dbt; workflow managers: Airflow; event streaming: Kafka; large-scale processing: Spark), storage (data warehouse, data lake) and data usage (data science platforms, ad hoc query engines, real-time analytics, dashboards and analytics).
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What this slide does
“Data is huge and growing, with commercial open source everywhere in the stack” gives the deck a concrete market claim. Data is huge and growing, with COSS omnipresent in data infrastructures. Stack map across data sources (OLTP DBs via CDC, applications/ERPs, event collectors, logs, third-party APIs, file and object storage), ingestion and transformation (connectors: Fivetran, Airbyte - we are here; data modeling: dbt; workflow managers: Airflow; event streaming: Kafka; large-scale processing: Spark), storage (data warehouse, data lake) and data usage (data science platforms, ad hoc query engines, real-time analytics, dashboards and analytics). Its job is to make that part of the argument easy to grasp before the narrative advances to the next point.
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