Great Expectations offers GX Cloud, an end-to-end data quality platform that utilizes an Expectation-based approach to testing, enabling organizations to establish verifiable assertions about their data. This solution enhances data integrity and collaboration by providing a unified framework for monitoring data quality across various business functions, ensuring reliable input for critical decision-making.
Funding
$65M 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
Data quality issues can lead to unreliable insights and flawed decision-making across various business functions. Maintaining data integrity requires a comprehensive and collaborative approach to data testing and monitoring. Existing solutions often lack the accessibility and integration needed to involve both technical and non-technical stakeholders in the data quality process.
Solution
GX Cloud is an end-to-end data quality platform that empowers organizations to establish verifiable assertions, known as Expectations, about their data. By providing a unified framework for data quality testing, GX Cloud enhances data integrity and promotes collaboration between technical teams and business stakeholders. The platform seamlessly integrates with existing data stacks and deploys throughout the data pipeline to pinpoint data quality issues. Its SaaS interface and plain-language approach make it accessible to a wide range of users, enabling critical input from both technical and non-technical stakeholders.
Target Audience
The primary audience includes data engineers, data scientists, data analysts, and other data professionals who need to ensure the quality and reliability of their data, as well as business stakeholders who rely on data-driven insights.
Features
- Expectation-based testing: Define verifiable assertions about data to ensure quality.
- End-to-end solution: Comprehensive coverage from exploratory data profiling to continuous monitoring.
- Seamless integration: Integrates with existing data stacks and deploys throughout the pipeline.
- SaaS interface: User-friendly interface accessible to both technical and non-technical teams.
- Scalable architecture: Easily scales to accommodate growing data needs.
- Historical results: Maintains a complete history of data quality tests and results.