ETL has lost the race to big data. The solution is as simple as reordering the phases of traditional process integration. Let us rewind to 1989 when the internet happened to the common computer user.

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, ...

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 ...

As healthcare organizations increasingly embrace cloud platforms, the complexity of managing data migration has become a critical challenge. The Extract, Transform, and Load (ETL) process, a ...

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 ...

In today's IT landscape, information is crucial. Any business, could be a startup or an established one, requires relevant data or information to make better business decisions, manage sales ...

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 ...

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 ...

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 ...