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Databuck

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Software Status:Active

About Databuck

DataBuck is a data quality software from FirstEigen that automates profiling, testing, and observability for enterprise cloud data. It includes data quality and trust, data matching, and data remediation so organizations can trust their data for analytics and decision-making. Specifically designed for enterprise needs, DataBuck uses AI-driven insights to ensure data accuracy and reliability, addressing issues that can lead to poor analytics outcomes. Users can access resources such as blogs, white papers, and webinars for additional learning. Key capabilities: data quality and trust data matching data remediation profiling testing Best for: enterprises that need reliable data quality management to support informed business decisions.

Databuck Details

Vendor
FirstEigen
Year Launched
Location
1212 S Naper Ste 119-220 Naperville, IL 60540
Deployment
cloud, on premise, linux
Training Options
documentation, videos, live online, in person
Countries Served
All Countries
Languages
English
Users
Data Analysts, Data Scientists, Database Administrators, IT Managers, Business Intelligence Analysts
Industries Served
Healthcare, Education, Finance, Retail, Manufacturing, Technology.
Tags
Data quality, Data trust, Data observability, Data validation, Artificial intelligence in data, Machine learning for data, Data remediation, Autonomous data operations, Big data tools, Cloud data platforms, Data governance, Data integrity, Data pipeline monitoring

Databuck's In-App Market Place

Does Databuck have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

0

Mini Apps

Pricing Options

Free trial
Free version
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Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (Fr), CNY (¥), SEK (kr), INR (₹), SGD (S$), HKD (HK$), NZD (NZ$), KRW (₩), NOK (kr), MXN (Mex$), RUB (₽), ZAR (R), BRL (R$), TRY (₺), AED (د.إ), SAR (ر.س)

Pros & Cons

  • Continuous Trust Scoring: Provides enterprise-grade confidence in data quality
  • Scalable & Cloud-native: Supports AWS, Azure, Spark ecosystems
  • AI Remediation Agents: Proactively fix data, not just detect issues
  • No public pricing transparency – may hinder small-Business interest
  • Limited language support – currently only English interface
  • Potential latency – needs cloud resources and ML processing
  • New features in preview – autonomous remediation still in development

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