Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Discover the reasons why leading companies are turning to the Crux external data automation platform to enhance their external data integration, transformation, and monitoring without the need for additional personnel. Our cloud-native technology streamlines the processes of ingesting, preparing, observing, and consistently delivering any external dataset. Consequently, this enables you to receive high-quality data precisely where and when you need it, formatted correctly. Utilize features such as automated schema detection, inferred delivery schedules, and lifecycle management to swiftly create pipelines from diverse external data sources. Moreover, boost data discoverability across your organization with a private catalog that links and matches various data products. Additionally, you can enrich, validate, and transform any dataset, allowing for seamless integration with other data sources, which ultimately speeds up your analytics processes. With these capabilities, your organization can fully leverage its data assets to drive informed decision-making and strategic growth.
Description
MatchX offers a comprehensive AI-enhanced data quality and matching solution that revolutionizes how companies manage their information assets. By integrating powerful data ingestion capabilities and intelligent schema mapping, MatchX structures and validates data from diverse sources, including APIs, databases, and documents. The platform’s self-learning AI models automatically detect and correct inconsistencies, duplicates, and anomalies, ensuring data integrity without intensive manual intervention. MatchX also provides advanced entity resolution techniques like phonetic and semantic matching to unify records with high precision. Its role-based workflows and audit trails facilitate compliance and governance across industries. Real-time AI-driven dashboards deliver continuous monitoring of data quality, trends, and compliance status. This end-to-end automation enhances operational efficiency while reducing risks associated with poor data. Built to handle massive data volumes, MatchX scales effortlessly with evolving business demands.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
Apache Kafka
No
Collibra
No
Google Cloud Platform
Yes
Looker
No
Microsoft Azure
Yes
Microsoft Power BI
No
PostgreSQL
No
SQL
Yes
Integrations
Amazon S3
No
Amazon Web Services (AWS)
No
Apache Kafka
Yes
Collibra
Yes
Google Cloud Platform
No
Looker
Yes
Microsoft Azure
No
Microsoft Power BI
Yes
PostgreSQL
Yes
SQL
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Crux
Founded
2017
Country
United States
Website
www.cruxdata.com
Vendor Details
Company Name
VE3 Global
Founded
2010
Country
United Kingdom
Website
www.ve3.global/matchx/
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
ETL
Data Analysis
No
Data Filtering
No
Data Quality Control
No
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Product Features
Data Quality
Address Validation
Yes
Data Deduplication
Yes
Data Discovery
No
Data Profililng
Yes
Master Data Management
Yes
Match & Merge
Yes
Metadata Management
Yes