Extraction, transformation and load (ETL) became a familiar concept in the 1990s, when data warehousing became a well known business intelligence (BI) concept. The advent of the web, and the vast ...

Co-Founder & CTO of Datametica Solutions, leading the company's long-term technology vision and ensuring alignment with business strategy. With the advantages of scalability, enhanced performance and ...

Moving data between applications and warehousing data for analysis are recurring issues for app builders, data engineers, and IT teams. But we all know our businesses can benefit in significant ways ...

Maria Anurag Reddy Basani, a seasoned expert in data engineering and analytics, has made significant strides in the field over the past decade. With experience spanning industries such as insurance, ...

Katta's expertise in optimizing ETL workflows and implementing data quality frameworks can serve as a blueprint for successful data transformation initiatives. In a world where data is increasingly ...

Every data integration initiative-whether it supports better decision making, a merger/acquisition, regulatory compliance, or other business need-requires a set of processes to be completed before the ...

In this data-driven age, enterprises leverage data to analyze products, services, employees, customers, and more, on a large scale. ETL (extract, transform, load) tools enable highly scaled sharing of ...

The processing needed to populate a data warehouse is generically referred to as “ETL.” ETL originally stood as an acronym for “Extract, Transform, and Load.” Those three kinds of actions were ...