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Non-development tasks take up the vast majority of your time as an analytics engineer.

For an enterprise team working on dozens of projects at a time and meeting new requirements, we estimate 60% wasted effort and time on such tasks.

Often, engineers have to make assumptions about data, and test these assumptions in a trial-and-error manner. It’s time to use a workflow that speeds up the process.

GenAI struggles when you expect it to provide all the answers. Plus, you’re shut out from the process — creating an analytics ‘black box’.

Ellie’s structured workflow combines the speed of modern genAI and human input to improve the quality of results.

You can “reverse engineer” your data warehouse into Ellie, and our AI agent will generate a description for each table and each column in the table.

You’ll always have a business expert who can understand the meaning of the data you’re working on.

Ellie gives you the ability to understand data and create connections using ER diagrams, using an UI that was developed for pace.

Each diagram — representing your source data warehouse or a stage layer based on one or more sources — then becomes a reusable model that represents your dbt project.

Plus, as a team and a data organization, you have a more transparent data analytics design process to follow.

Ellie’s visual interface doesn't exist in isolation. You can connect what you do in Ellie to dbt to create the source and stage layers of your dbt project.

This gives you a head start for your analytics project, with a clear understanding of source data.

All the documentation you need for your project is automatically created as well. Our research suggests that you can meet your analytics KPIs up to 60% faster.