TechPrufer
Sign inGet started

Blogs›GitLab›Meltano Data Platform

Meltano Data Platform

Meltano Data Platform

3
posts
2018

Meltano is a product designed to be a complete solution for data teams, encompassing the data science lifecycle (model, extract, load, transform, analyze, notebook, orchestrate). It aims to bring software development best practices to data analytics, enabling version control, pipeline tracking, and making analytics accessible to a wider audience. Initially supporting Postgres and planning for Snowflake, Meltano focuses on managing data integrations and providing a more stable and process-driven approach. This post introduces two user personas (users with engineers on staff and users without), highlights the need for both CLI and GUI interfaces, and emphasizes the role of Meltano as the 'glue' between extractors and loaders based on Singer specifications. It also discusses the team's focus on building extractors and loaders, improving the CLI user experience with UX collaboration, and seeking frontend contributions. The team is also adopting a 'dogfooding' approach to better understand user pain points and has implemented embedded engineers to improve cross-functional understanding and problem-solving.

2018

New Meltano personas, priorities, and updates from the team

10/8/2018

This post introduces two user personas for Meltano: users with dedicated engineers and users without. It highlights the need for both CLI and GUI interfaces, with Meltano acting as the 'glue' for Singer-based extractors and loaders. The team is focusing on building more extractors/loaders, improving the CLI UX with UX team collaboration, and seeking frontend contributions. A 'dogfooding' approach is being adopted to experience user pain points directly, and embedded engineers are being used to foster cross-functional understanding.

Thanks for all the feedback and interest in Meltano!

8/7/2018

This post details the initial feedback and next steps for Meltano, an open-source data integration and analytics tool. It highlights the team's commitment to building common core extractors (e.g., Salesforce, Marketo, Zendesk) and applying Meltano to machine learning projects. It also clarifies that Meltano can be used selectively and that the team plans to leverage GitLab CI for orchestration, with potential contributions to CI for features like sub-pipelines and DAGs. The post also discusses the vision for the monorepo and the benefits of using Docker images for customization.

Hey, data teams - We're working on a tool just for you

8/1/2018

This post introduces Meltano as a new product for data teams, aiming to fill gaps in understanding business operations effectiveness by expanding the common data store. It details the problem Meltano solves, which is the current fragmented approach to data analytics using separate tools, and highlights the goal of making analytics accessible to everyone. It also outlines contribution opportunities in areas like UI, Extractors, and Loaders, and mentions initial database support for Postgres with Snowflake planned.