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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Mind Foundry
Date Founded
2016
Company Location
United Kingdom
Company Website
www.mindfoundry.ai/
Company Facts
Organization Name
Bain & Company
Date Founded
1996
Company Location
United States
Company Website
www.bain.com/vector-digital/
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Fraud Detection
Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Crypto
For Insurance Industry
For eCommerce
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval
Insight Engines
AI / Machine Learning
Augmented Analytics
Data Aggregation
Data Classification
Data Extraction
Data Source Connectors
Full Text Search
Intent Recognition
Multiple Data Sources
Search / Filter
Sentiment Analysis
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Pricing Optimization
Channel Analysis
Competing Product Analysis
Forecasting
Market Analysis
Multi-Store Management
Price List Management
Price Optimization Automation
Pricing Analytics
Profitability Analysis
Scenario Planning
Categories and Features
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization