"A notebook with visual, low-code, and SQL tiles. Every tile compiles to SQL, so your work will never get stuck in a proprietary format."
Founded by Jenica Zhong and Jessica Fang
Problem
1. SQL is verbose and hard to use for exploratory data analysis
Data analysis is an iterative and investigative process. While SQL remains the most powerful language for working with data, SQL syntax results in long code blocks that are unforgiving when trying to quickly explore data.
2. Plain English is good for describing a high level query, but not the right UI for refinement
AI has been an incredible technology for fetching the right general data and columns on a well-defined and metadata-rich semantic layer. However, analysts must write long descriptive sentences to refine the query.
Solution
Tile allows anyone to explore and investigate their data in modularized steps without the clunky syntax of SQL.
Once the insight is found, convert your tiles to a SQL block so you still have the robustness of code when building reports to share this insight with others.
Vision: The future is AI-enabled data analysis and report building. However, for it to work, explainability will be key. Tile will allow AI to show its work with step-by-step tiles and allow end users to fine-tune its responses.
Demo: Learn how Dwight can use Tile to explore Dunder Mifflin’s transactions data ⤵️
Learn More
🌐 Visit tile.sh to learn more
📅 Sign up for a free 14-day trial using Tile with your data!
🤝 Reach out to Jenica for specific questions
👥 Follow Tile on LinkedIn & X
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