Cycles of innovation in data management and analytics appear to drive classic ETL (Extract-Transform-Load) functions to a reversal, ELT (Extract-Load-Transform). The implications of this reversal ...

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are two different types of processes to move data from a source system to a destination system. ETL extracts raw data from a source ...

Changes in data warehousing result in changes and developments in the supporting processes, applications and technologies. As such the origin, growth and decline of ETL can be mapped directly against ...

Despite the advances we’ve made in data science and advanced analytics in recent years, many projects still are beholden to a technological holdover from the 1980s: extract, transform, and load, or ...

Not all data lakes are created equal. If your organization wants to adopt a data lake solution to simplify and more easily operate your IT infrastructure and store enormous quantities of data without ...

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 ...

The rapidly changing world of data engineering has seen a significant shift with the combination of Apache Spark, Snowflake, and Apache Airflow. This trio allows organizations to build highly ...

Data virtualisation is emerging as a possible technique for businesses to use in tying together disparate databases to become more agile in both their business operations and their data integration ...

Informatica (NYSE: INFA), an enterprise cloud data management leader, today launched the industry's only free cloud data loading, integration and ETL/ELT service - Informatica Cloud Data ...