Your ultimate data cloud observability solution
Reduce complexity of your data infrastructure and receive
the most precise Snowflake-specific column-level lineage and catalog on the market
in just 10 minutes

For your Snowflake data engineering teams
See how DWH helps its customers
Better Data Governance
By providing a comprehensive view of data assets and their relationships, DWH.dev provided data lineage and data catalog enable enterprises to establish and enforce data governance policies more effectively, to mitigate risks associated with data, and to improve overall data management.
Increased Efficiency and Productivity
Our solution helps enterprises to reduce the time and effort required for data analysis and decision-making. By providing a clear and complete view of data assets, our clients can quickly locate and the data they need, reducing the time required for data preparation and analysis. This will lead to increased efficiency and productivity, and making faster and better-informed decisions.
Improved Data Quality
DWH.dev help enterprises to ensure the accuracy and completeness of their data. We enable our customers to identify data quality issues, such as missing or inconsistent data, and take corrective actions to resolve them.
Awesome UI to keep everything under control

Powerful features for your goals
Visualize and understand your data
Understand your data and its interconnectivity through our brand new custom path view. This is one of our powerful tools for observation of your data, improving efficiency, and driving better business outcomes.

Easy to find - easy to improve
Improve your teams’ efficiency and productivity by reducing the time spent searching for metadata, allowing them to focus on other tasks.

Built to scale
Our solution is built to scale as your data needs grow. Whether you need to manage a few dozen data sources or thousands, our solution can handle it, thanks to a robust architecture that is designed to accommodate a wide range of data objects.

Quick start in minutes
Integrate DWH.DEV with your Snowflake database in minutes through enriching the metadata with your DBT manifest in one click. Upload ETL or BI SQL scripts from any sources: query history, GIT, Airflow, Looker, Power BI, etc. Or simply use DWH.DEV API for automation.

What users are saying about us
Take a look at reviews from users who have used DWH.DEV to observe and analyze their data. We believe that by sharing experiences and learning from each other, we can achieve superior outcomes.
Reviewing data lineage manually is quite cumbersome and takes time. With your solution, we are able to acquire knowledge about database models and fix potential data issues early in development, reducing turn-around time for client requests. We are excited to see how we can further increase data observability with DWH.DEV’s platform.

Fedor Zevako
Principal ConsultantPMSquare, Singapore
Data accuracy can make or break a business. With DWH.DEV, I can be sure where the data is coming from, where it is used and how it is transformed along the way.

Vit Lilich
Senior Data DirectorUSA
DWH.DEV is an advanced data lineage solution that provides critical insights and ultimately leads to better business decisions.

Igor Vasilcovsky
Executive DirectorGlobal US Bank, USA
I’ve tried to implement SQL parser for Snowflake myself, but I gave up on the idea quickly due to the complexity of the Snowflake dialect and the high frequency of changes, as it requires a tremendous amount of effort to create and maintain such a project. DWH.DEV offers more Snowflake-specific database insights than any other visualization solution that I’ve used. It is very relevant for my work as a Senior Data Engineer, and I am very impressed in my interactions with the team.

Vitaly Markov
Senior Data Engineerex Badoo, Bumble, UK
How to start and automate data observability in minutes
- Sign in, upload your metadata and start to use DWH.dev right now without any restrictions or payments.
- Get in touch with us
- We help you with the onboarding to unveil the full power of DWH.dev
If you want to figure out how to:
- make your data engineering teams more efficient
- understand and trust your data
- improve your data experience in minutes