Validio

Validio

Real-time data validation and data quality monitoring for modern data teams.

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Financials

Estimates*

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Revenues, earnings & profits over time
EUR201920202021202220232024
Revenues000000000000000000000000
% growth-----385 %
EBITDA000000000000000000000000
Profit000000000000000000000000
% profit margin----(5575 %)(1725 %)
EV000000000000000000000000
EV / revenue00.0x00.0x00.0x00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x00.0x00.0x00.0x
R&D budget000000000000000000000000

Source: Company filings or news article

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More about Validio
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Validio.io is a data management platform that helps businesses maximize the utility of their data. The company operates in the data analytics market, serving clients who need to process large volumes of data and extract valuable insights from it. Their clients range from small businesses to large enterprises across various industries.

Validio.io's primary offering is the Data Trust Platform, a comprehensive tool that allows businesses to prioritize, validate, and improve their data. The platform uses machine learning to identify and resolve data quality issues, both obvious and subtle. It also provides auto-generated field-level lineage for root cause analysis and incident resolution, enabling businesses to understand their data better and assign data ownership accurately.

The company's business model is likely based on a subscription or usage-based pricing model, where clients pay for the platform and any additional services they use. This model allows Validio.io to generate a steady stream of revenue while providing clients with a valuable tool to enhance their data management and analytics capabilities.

Validio.io's platform is highly regarded by data teams for its ability to process hundreds of millions of records per minute and proactively identify data issues. This proactive approach allows businesses to address data issues promptly, improving their overall data quality and the insights they can derive from it.

Keywords: Data Management, Data Analytics, Machine Learning, Data Quality, Root Cause Analysis, Incident Resolution, Data Ownership, Subscription Model, Proactive Issue Identification, Large Volume Data Processing.

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