Meltano

🚀 Exciting News! We've officially crossed the 5,000 mark on the Meltano Slack community! 🎉 A huge thank you to our incredible community members for your continuous support, engagement, and contributions. Together, we're making strides in the world of data integration and analytics. 🐉 Join us in the Slack community to connect, collaborate, and grow with fellow data, metrics and analytics enthusiasts. https://lnkd.in/ebs6-26Z #Meltano #DataIntegration #DataAnalytics

When it comes to data integration, people usually mention Fivetran, Airbyte, and custom Python scripts. I’ve been using Meltano since 2020 and decided to write an objective review. TL;DR: I love it, but there might be better tools for you. Meltano relies strongly on Singer and Apache Airflow. It is open-source, and you are responsible for deploying it scalable. It has an extensive plugin architecture, but some plugins may not work well for you. In addition to the text review, I included a quiz to help you decide whether Meltano is the right tool for you. Please share your opinion and experience. https://lnkd.in/dmj_ungN — #dataengineering #analyticsengineering #dataops #dataplatform #dataintegration #singer #airflow

We're happy to share that our Slack community for data best practices and open source data stacks and Meltano now has over 4,000 members! So.... if you want to discuss - How to deal with the ELT vs ETL debate - How to best test your specific data pipeline - How to deploy dbt & Meltano together on GitHub Actions to save 80% of your data stack cost - Or anything else data-related Join https://meltano.com/slack today!

The Meltano Slack community is back! Sign in with your existing account on https://meltano.slack.com, sign up on https://meltano.com/slack, or browse anonymously on https://lnkd.in/eBetX5am. Thanks for your patience & Happy New Year!

The Meltano Slack community is currently inaccessible as the result of a botched migration by Slack: https://meltano.com/slack Slack gave us 3 unviable options: 1. Pay $10,000s/month for 4,200+ enterprise seats (instead of the 20 for our team that we'd agreed to) 2. Engage Slack in a "pretty costly" "4 week minimum" "downgrade" project 3. Start from 0 with a new Slack community We're really sorry for the inconvenience and hope that Slack can resolve this in a reasonable and timely fashion. If you know anyone at Slack who could help, we'd appreciate it if you could let them know you're locked out of one of your favorite data communities and share this with them. We appreciate your patience as we get you back your Slack! Stewart Butterfield Marc Benioff Junan Pang

This Wednesday! Join us at #OSAcon as Pat Nadolny discusses ETL in the LLM app ecosystem. Explore Singer and the Meltano community, new data pipeline needs in the AI space, and how we can apply data engineering principles to solve them. Learn more and sign up today for this free and virtual event. https://osacon.io/ #LLM #DataEngineering

The data science field is growing rapidly, with new roles and technologies emerging constantly. With companies collecting more data than ever before, data management, processing, and storing are becoming more complex by the day. Learn more about data engineering and data science 👇 https://bit.ly/3sf9JJy #DataScience #Enginering #ML

Unless you're the Elle Woods of the data world, testing data applications is hard. Get a walkthrough of some common challenges that data teams face when testing data applications: https://bit.ly/45775n6 #DataOps #DataEngineering

Explore new data pipeline needs in the AI space with Pat Nadolny, Senior Data Engineer at Arch, the creators of Meltano, at #OSACon. Check out the full agenda and register for this free and online event! https://osacon.io/ #DataEngineering #AI

Want a simpler data pipeline process? 🙋 See how Rahul Soni integrated DuckDB, dbt, Meltano, and Streamlit to create an all-in-one modern Data Stack (which can be used on your laptop, no less!) 🧑💻 https://bit.ly/49XSfD4 #DuckDB #DataPipelines