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Data version control is a method of working with data sets. It is similar to the version control systems used in traditional software development, but is optimized to allow better processing of data and collaboration in the context of data analytics, research, and any other form of data analysis.
ML model checkpoints versioning: The new release also enables versioning of all checkpoints with corresponding code and data. Metrics logging: DVC 2.0 introduced a new open-source library DVC-Live that would provide functionality for tracking model metrics and organizing metrics in a way that DVC could visualize with navigation in Git history.
lakeFS is a data versioning engine that manages data in a way similar to code. By using operations such as branching, committing, merging, and reverting, which resemble those found in Git, it facilitates the handling of data and its corresponding schema throughout the entire data life cycle.
MarkLogic introduced bitemporal data support in version 8.0. Time stamps for Valid and System time are stored in JSON or XML documents. [2]XTDB [3] (formerly Crux) is an open source database that indexes documents using an EAV data model and provides point-in-time bitemporal SQL & Datalog queries.
Team Foundation Version Control [proprietary, client-server] – version control system developed by Microsoft for Team Foundation Server, now Azure DevOps Server; The Librarian [proprietary, shared] – Around since 1969, source control for IBM mainframe computers; from Applied Data Research, later acquired by Computer Associates
(Reuters) - Data analytics firm Palantir Technologies and defense tech company Anduril Industries have partnered to use defense data for artificial intelligence training, the companies said on Friday.
The study analyzed data from nearly 10,000 people who were enrolled in a randomized clinical trial, looking into the impact of low-dose aspirin on reducing heart disease risk in Australian and ...
Prepare the schema so that it can hold data in both the old and new formats. This might mean adding a new version of a column or a table, without affecting existing data. Deploy a new version of the application which writes data in both the old and new formats (hence the name dual writing). It's important to ensure consistency of these writes ...