When I test-drove Upsolver for a consulting company, I used it in POC to stream and ingest data. The goal was to move data from a source, possibly SQL Server, into a destination like Snowflake or Redshift. The POC aimed to evaluate Upsolver against StreamSets, the competition for ETL tasks. The use case involved data aggregation, ingestion rules, landing data into a data lake, and handling ETL processes for a data warehouse.
What is data integration? Data integration is the process of combining data that resides in multiple sources into one unified set. This is done for analytical uses as well as for operational uses.
When I test-drove Upsolver for a consulting company, I used it in POC to stream and ingest data. The goal was to move data from a source, possibly SQL Server, into a destination like Snowflake or Redshift. The POC aimed to evaluate Upsolver against StreamSets, the competition for ETL tasks. The use case involved data aggregation, ingestion rules, landing data into a data lake, and handling ETL processes for a data warehouse.