Count is a canvas-based business intelligence tool that integrates SQL, Python, and low-code capabilities to enable data teams to explore and visualize data collaboratively. It addresses the inefficiencies of traditional dashboarding tools by providing a flexible workspace that enhances data accessibility and fosters real-time insights across teams.
Funding
$7.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional business intelligence (BI) tools often isolate data teams, turning them into support functions that struggle to provide actionable insights. Existing dashboarding solutions can lead to a lack of trust in data, create chaotic reporting environments, and fail to address the ad-hoc data requests from various business units. This ultimately hinders data teams from driving business improvement and demonstrating a clear return on investment.
Solution
Count offers a canvas-based BI tool that integrates SQL, Python, and low-code capabilities, enabling data teams to explore, visualize, and collaborate on data analysis within a unified workspace. By combining the functionalities of a whiteboard, dbt IDE, data notebook, and traditional BI tool, Count fosters transparency and collaboration across data engineers, analysts, and business stakeholders. The platform allows users to build metric trees and process flow maps, providing context to metrics and aligning teams around a common understanding of performance drivers. Count empowers analysts to solve complex problems with data by offering flexible exploration and governed self-service capabilities, ensuring that business decisions are based on trusted data.
Target Audience
Count is designed for data teams, including data engineers, data analysts, and business intelligence professionals, within organizations seeking to improve data accessibility, foster collaboration, and drive business improvement through data-driven insights.
Features
- Canvas-based interface for flexible data exploration and visualization
- Integration of SQL, Python, and low-code cells for diverse analytical approaches
- Real-time collaboration features, including comments, sticky notes, and discussion threads
- Metric layer for defining and governing metrics across the organization
- Automated alerts via Slack and email based on custom schedules or trigger events
- Version control for managing changes and ensuring data integrity
- AI-powered query assistant to streamline data exploration
- Connects to various data sources, including Athena, Azure Synapse, BigQuery, Databricks, MySQL, PostgreSQL, Redshift, Snowflake, and SQL Server