Data Validation

Validate and govern your data before using it. Data Validation automatically analyzes the structure, quality, sensitivity, and traceability of your datasets to help you identify issues, reduce risks, and prepare data for analytics, artificial intelligence, and secure data sharing.

Turn any dataset into a reliable
production-ready asset

Data Validation automates inspection, cleansing, profiling, and risk analysis so teams can quickly understand the true state of their data and make decisions with greater confidence.

Automatic analysis from the very beginning

Every dataset is automatically inspected upon ingestion, generating a complete technical view of its structure and content.

Automatic detection of formats, encodings, and structures
Analysis of rows, columns, headers, and technical metadata
Support for tabular data, documents, images, audio, and video
Optimized processing for datasets with millions of records

Automatic analysis from the very beginning

How does it work?

Dedomena.AI automates data validation and understanding so you can work with trusted information from day one.

Import the dataset

Upload data from local files, URLs, or enterprise connections and add it to your Workspace.

Automatically analyze the information

The platform inspects the file structure, extracts technical metadata, detects issues, and generates an initial quality assessment.

Understand data behavior

Access profiling views, visualizations, risk analysis, AI-generated insights, and privacy assessments from a single environment.

Validate and prepare the dataset

Apply transformation rules, enrich metadata, and prepare the dataset for analytics, sharing, or artificial intelligence initiatives.

Benefits

Understand the true state of your data. Gain a unified view of the content, structure, quality, and sensitivity of every dataset.

Detect issues before they impact your projects

Identify structural errors, anomalies, sensitive information, or potential biases before using the data.

Improve trust in AI processes

Work with documented, traceable datasets that are ready for training and validating AI models.

Reduce regulatory risks

Facilitate compliance processes through automated privacy assessments and audit documentation.

Increase traceability and governance

Maintain a complete history of transformations, analyses, and changes applied to every dataset.

Generate documentation automatically

Produce quality, risk, and profiling reports ready for review, sharing, or regulatory compliance.

Use Cases

Data Preparation for Artificial Intelligence

Validate and understand datasets before training, evaluating, or monitoring AI models.

Data Governance and Quality

Centralize quality metrics, traceability, and sensitivity indicators to improve data lifecycle management.

Compliance and Privacy

Identify sensitive information and document data processing activities before sharing data.

Dataset Publishing and Sharing

Ensure quality, documentation, and privacy standards before distributing information.

Data Modernization and Migration

Assess the quality and structure of data originating from legacy systems.

Data Products and Monetization

Increase the trust and value of data assets through objective metrics and comprehensive documentation.

Ready to truly understand your data?

Transform unknown datasets into reliable, documented, and AI-ready assets through automated validation, advanced profiling, and integrated governance.