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Hi HN, I’m Joe. I’m a data engineer, and I built Datachef because I got tired of maintaining the disjointed data stack (Fivetran, Airbyte, Airflow, Snowflake, Redshift, S3, dbt, Looker, Tableau, a reverse-ETL tool, etc.)…
Hi HN, I’m Joe. I’m a data engineer, and I built Datachef because I got tired of maintaining the disjointed data stack (Fivetran, Airbyte, Airflow, Snowflake, Redshift, S3, dbt, Looker, Tableau, a reverse-ETL tool, etc.) and being a middleman for business users that just wanted to self serve. Datachef is one managed platform where you can: - Connect your business systems (Salesforce, Marketo, Hubspot, etc.) and/or databases (Postgres, MySQL) in a few clicks. Your data lake is synced in minutes. - Explore your data via natural language or write SQL directly. - Model how data is combined, filtered and aggregated. Create a shared system of intelligence. - Share models across the org so every query, report and slide deck tells the same story. - Integrate data back into Salesforce, Marketo and HubSpot — lead scores, segments and events, in the systems your team already works in. We shipped a Claude connector ( https://www.datachef.com/blog/datachef-claude-connector ). From Claude you can run complex, multi-step/multi-dataset analysis, and create or update your models and sync settings. I’d love feedback, especially from anyone who has run the modern data stack and has opinions on what consolidating it should and shouldn’t give up.
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