Ten years ago, we started a hot sauce company, Bacon Hot Sauce, together. But more relevantly, we have spent the last two decades building data pipelines at startups like Clover Health, Eaze, Opendoor, Playdom, and Zenefits. For example, at Yammer, we built a tool called “Avocado,” which was our end to end analysis tool chain -- we loaded data from our production database and relevant SaaS tools like Salesforce, we scheduled data transformations (similar to Airflow), and we had a front-end BI tool where we wrote and shared queries and dashboards. Today Avocado is two tools, Mozart Data and Mode Analytics (a collaborative analytics tool). We basically have been building similar data tools for years (though the names and underlying technologies have changed).
Dan & I decided to build a product to bring the same tools and technology to earlier stage companies (so that you don’t need to make an early hire in data engineering). We’ve built a platform where business users can load data and create & schedule transformations with just SQL, wrapped in an interface anyone can use -- no Python, no Jinja, no custom language. We connect to over 150 SaaS tools and databases, most just need credentials to send data to Mozart. There is no need to define DAGs (we parse your SQL transforms to automatically infer the way data flows through the pipeline). Mozart does the rote and cumbersome data engineering that typically takes a while to set up and maintain, so that you can tackle the problems your company is uniquely suited to do.
Most data companies have focused on a single slice of the data pipeline (ETL, warehousing, BI). The maturation of data tools over the last decade has made now the time to combine them into an easy solution accessible to data scientists and business operations alike. We believe that there is immense value in centralizing and cleaning your data, as well as setting up the core tables for downstream analysis in your BI tool. Customers like Rippling, Tempo, & Zeplin use Mozart to automate key metrics dashboards, calculate CAC and LTV, or identify customers at risk of churn. We want to empower the teams -- like revenue and sales ops -- that have a lot of data, know what they want to do with it, but don’t have the engineering bandwidth to execute it.
Try us out and see for yourself - you can sign up (https://app.mozartdata.com/signup) and immediately start loading, querying, cleaning, and analyzing your data in Mozart. We offer a free 14-day trial (no credit card required). After the free trial, we charge metered pricing based on compute time used and data ingested. We’d love to hear about your experiences with data pipelines and any ideas/feedback/questions you might have about what we’re building.