Data Quality
Sort is the only platform that enables engineering best practices for improving data quality.
Engineering best practices include:
Making data easy to find, query, and browse through data discovery, to incentive more data quality issues and proposed fixes
Easily tracking data issues through creation to resolution
Resolving data issues with approval workflows, through data change management
Navigate databases with the ease of a webpage
Imagine searching for tables in all databases across your organization, immediately running queries and then copying a link to a specific rows to share with your team - these are the kind of features we take for granted with code on Github but are extremely difficult with any database. Instead of writing steps in plain text for how a user can find this data, simply use Sort to link to it.
Get the whole team creating data issues
Sort makes it easy for anyone in your organization, regardless of team or technical abilities, to create data Issues. Save time by using Sort to find the database owner, query the database, and report Issues. Stop copying data inconsistencies over to yet another tracking system, simply use Sort to meet these needs.
Resolve data issues with Change Requests
Explore Other Use Cases
Data Discovery
Sort centralizes hundreds of databases into a single platform, making databases accessible and easy to track...
Data Issue Management
Let's face it. Tracking data issues is painful. Beyond just the repetitive practice of cutting and pasting queries between...
Data Change Management
Managing data changes is time consuming and error prone. Data changes are often done in isolation, wi...
AI and LLMs
When it comes to leveraging your organizations data for AI and LLMs, data quality is extremely important. Sort helps...

Github workflows for your database

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