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Rivery Debuts ETL Python Integration, A First In The Industry
Fremont, CA: Rivery, a leading data management company, launched integration of Python as a native source or target for any data process, giving data analysts and engineers full control over complicated data workflows. This industry-first solution, which is currently available to all Rivery customers, allows Python DataFrames to be utilized as a native source or target in ETL/ ELT workflows without needing any Python "plumbing" code.
Previously, companies wishing to construct an end-to-end data stack had to pick between a "no-code" platform that was simple to use or a complicated solution built for engineers that supported advanced use cases and customization. While Rivery's no-code solution handled most of the issues faced by data analysts and BI teams, adding Python addresses more sophisticated requirements like custom connectivity, complicated transformations, AI/machine learning, and data enrichment.
LEIT DATA, a specialist data and analytics company with an emphasis on offering DataOps solutions is one of Rivery's data partners. LEIT DATA recently used Rivery's new Python integration to build a platform for one of its media clients. LEIT DATA Co-Founder Chris Tabb stated: "Our client's ability to use Rivery's Python integration to embed Python as part of a data pipeline was a game changer. It allowed us to deliver the client solution in less time and at a lower cost than any other option we had previously considered. You can get the most agility out of your data engineering team by managing all of the business logic of your end-to-end data pipeline within the Rivery platform."
Rivery's CTO, Aviv Noy, stated: "Python allows data engineers to create data pipelines that are as unique as their imaginations allow. Rivery users may now fully customize their data and augment it with machine learning and complicated transformations thanks to the advent of Python integration."