I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs. We primarily serve financial service customers in India and around the globe. We use Upsolver as an ETL tool to move data from different sources into one destination quickly and at scale.
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.
Data Integration solutions harmonize data from different sources, ensuring smooth data flow throughout an organization. They are essential in enabling consistent data analysis, fostering better decision-making, and driving efficiency.Data Integration empowers organizations by connecting disparate data systems, reducing duplication, and enhancing data quality. This process involves combining data from various sources and providing users with a unified view. Users benefit from reduced...
I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs. We primarily serve financial service customers in India and around the globe. We use Upsolver as an ETL tool to move data from different sources into one destination quickly and at scale.
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.