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 facilitates the combination of data from diverse sources into a unified view, crucial for businesses to make informed decisions and enhance operational efficiency. With comprehensive solutions available, organizations can streamline their data workflows. Data Integration solutions are vital for businesses aiming to handle large volumes of data efficiently. These solutions help in synchronizing data from multiple sources, ensuring consistent data across platforms, and...
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.