Data Pipelines
Automate Data Preparation
Datapot simplifies the data preparation process with its configurable data pipelines.
Automation made simple
User-friendly visual editor
Intuitive interface for building pipelines easily.
Drag-and-drop simplicity for seamless pipeline creation.
Ready-to-use and configurable building blocks
Simplify tasks like resizing images, transcoding videos, auto-labeling for AI models.
Data preparation simplified
From manual to magical:
Automate your workflows
Streamline and innovate without limits
Focus on Results.
Not repetitive Work.
Minimize human errors
Reduce manual effort and minimize human errors.
Ensure consistencty across data preperation tasks.
Boost productivity
Eliminate repetitive manual tasks.
Save time and focus on innovation.
Efficiency maximized
Instant pipeline execution
A pipeline executes immediately upon commit, performing the necessary actions to make data available in the repository as quickly as possible. The system operates in a highly parallelized manner, distributing tasks across multiple optimized nodes. For example, if a user commits numerous videos that need transcoding, the workload is spread across specialized nodes. This ensures results are available promptly, eliminating long waits associated with sequential processing or nightly batch jobs.
No more batch jobs.
No more chaos.
Data pipelines replace the need for numerous internal batch jobs that can become difficult to manage and require dedicated staff. These batch jobs and scripts often lack proper documentation, are spread across multiple systems, and are managed by individual team members, making them prone to becoming technical debt and posing significant risks.
By centralizing and automating these tasks, Datapot ensures that data transformations are performed automatically and inconsistencies are eliminated. Furthermore, computational deduplication ensures that each transformation is applied only once per file across all repositories. This not only saves time but also reduces computational costs.
Product
Data Version Control
Data Pipelines
Data Transfer
Datapot Query Language (DQL)
Metadata Support
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©2025 AItive Data GmbH. All rights reserved.
©2025 AItive Data GmbH. All rights reserved.
