Meet the Industry-First ETL Python Integration
Data engineers fret over data pipeline complexity. While you can say that it’s their primary job, building pipelines are becoming more challenging.
The biggest challenge is the data sources, which come in various forms and locations. New data sources, like IoT platforms, will add to the headache as these are coming online very quickly.
The answer for many DataOps teams is to build an end-to-end data stack. This meant they had to choose between an intuitive “no-code” platform that allows them to quickly focus on building pipelines or complex solutions that can help engineers customize complex data workflows.
Rivery is offering a bridge. It integrates Python as a native source or target for any data workflow. The company claims that it is an industry-first solution that allows data engineers using the company’s no code platform to use Python DataFrames as a native source or target in their ETL and ELT workflows.
According to the announcement, Rivery's no-code solution can tackle most of the challenges data analysts and BI teams face. Adding Python solves advanced needs, including custom connectivity, complex transformations, AI/machine learning, and data enrichment.
"Python frees data engineers to customize their data workflows as far as their imagination can go. The addition of Python integration empowers Rivery users with full customization and data enrichment with machine learning and complex transformation," said Aviv Noy, Rivery's chief technology officer.
LEIT DATA, a specialist data and analytics consultancy and a Rivery Partner, provides DataOps solutions. Recently, the company delivered a platform for one of its media clients using Rivery's new Python integration.
"Having the ability to embed Python as part of a data pipeline using Rivery's Python integration was a game-changer for our client. It enabled us to deliver the customer solution in less time and with less cost than any other alternatives we have used in the past. The ability to manage all the business logic of your end-to-end data pipeline within the Rivery platform allows you to get the best agility from your data engineering team," said Chris Tabb, co-founder of LEIT DATA.
Image credit: iStockphoto/iambuff
