A user proposes a change to a piece of data.
Sort lets anyone propose data changes and contribute to your overall data quality.
Not all data can be managed through automation. Some data is so valuable it still needs manual review and approval every time it changes. Sort is a platform that makes these manual data changes easy, efficient, and transparent.
Sort is a simple tool that solves a big problem in data management
These data changes are usually made through scattered, time-consuming, and unaccountable manual processes. Sort collects all these data changes in one place, streamlines everything, and makes the process 100% transparent.
Sort lets anyone propose data changes and contribute to your overall data quality.
Sort gives them a queue of data changes they can approve or deny in one click each.
Sort goes into your database and makes data changes for you - no SQL needed.
Sort creates a history of who changed your data, when they did it, and what changed, and why.
It’s time to try Sort. Schedule a demo today.
Sort helps with any data you still manage manually — which is often data that’s so refined, valuable, or sensitive it would currently be too difficult to manage through automation. Common examples include…
Sort lets front-line teams - who touch your data every day and know it best - identify and propose necessary changes. Teams like...
Sort connects directly to your databases and fits perfectly into the lives of your users, admins, and engineers. Sort is…
Creates one home for every user and step of manual data management.
Runs from a clean browser-based UI and lets users propose changes in natural language.
No SQL is needed — all approved data changes happen automatically in one click.
Offers a flexible API and out-of-the-box integrations with common DB’s.
Configures and enforces granular access controls to keep data safe and compliant.
It’s time to try Sort. Schedule a demo today.
Sort enables engineering best practices to improve data quality. If you're familiar with Github pull requests, Sort uses the same workflows for data changes. In addition to data changes, Sort makes it easy to report data issues and navigate databases, similar to GitHub repos.
Sort makes it simple to report issues on bad data values. After an issue is opened, a Change Request can be created to address the data issue and execute any fixes to the data (after an administrator approves and applies the Change Request via Sort's interface). The issue can then be closed after the bad data has been fixed by Sort.
Sort's long-term vision is to make databases accessible, whether within your organization or the world. We are making it easy to share, collaborate, and build on top of data.
Feel free to email us at info@sort.xyz, or reach out to us on Twitter (https://twitter.com/sort_xyz) We'd love to hear from you!
Supercharge customer support processes by making databases accessible. Sort adds guardrails to ensure data is checked by additional users, such as administrators, before any changes are made.
Suggest data changes
No SQL needed
Approval workflows
Safe for production systems
Sort is the only platform that enables engineering best practices for improving data quality. Report data issues, and resolve data problems with Change Requests, all within Sort.
Github workflows for data changes
Issue tracking for data problems
Improve communication
Link to specific rows and queries
Make internal teams vastly more efficient with Sort. Sort makes databases accessible and adds guardrails to ensure data is checked by additional users, such as administrators, before any changes are made.
No need to build admin panels or internal apps
Make databases accessible to more teams
Improve transparency for data changes
Approval workflows to ensure data changes are correct
Crowdsource data contributions, fixes, and improvements with Sort. Sort makes adding outside contributors for your database safe and easy.
Crowdsource data
Approval workflows to verify data changes
Leverage your community to fix data errors
Granular access control for internal and external teams
“Less than 50% of companies are confident in their internal data quality”
“An average of 4 working hours is being lost per employee per week in the IT department or data team due to the need to resolve issues related to preparing data for analysis”
“Every year, poor data quality costs organizations an average $12.9M.”