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Description
DataMatch Enterprise (DME) is Data Ladder's entity resolution and data matching platform. It identifies records that refer to the same person, business, or entity across disconnected systems, then links and consolidates them into a single accurate record. Core functions include data profiling, standardization, matching, deduplication, and merging, supporting use cases such as Customer 360, KYC, fraud detection, and master data management.
The platform is available through a no-code visual interface for business users and a REST API for developers, allowing the same matching engine to be embedded in applications, data pipelines, or AI agent workflows. Match results are rule-based and traceable, so users can see the specific logic behind each linked record rather than a single opaque score.
Recent additions include entity graphs for visualizing connected records, live search for real-time matching, and Docker as a deployment option in addition to cloud and on-premises environments.
Independent benchmarking across 15 studies shows DME identifying 5 to 12% more matches than comparable tools, with fewer false positives and accuracy up to 99%. In a large-scale test, it processed 10 million records in 41 minutes.
Description
Gain a comprehensive understanding of your data through various methods. While automatic profiling offers a foundational overview, enhanced functionalities cater to both technical and business users, enabling a more thorough exploration. With the integration of automation, pattern-based analysis, and statistical methods, you can acquire the in-depth insights necessary for informed decision-making. A broad array of rule-building tools empowers you to manage data quality across different tiers. You can assess standard metrics such as validity, completeness, consistency, accuracy, and timeliness, while also incorporating tailored metrics to fit specific needs. Advanced data quality is ensured through scenario-based rules that yield meaningful and context-sensitive results. Rectify data quality issues and enhance data for more significant insights, as automated correction features efficiently manage most tasks with consistent and traceable decision-making processes. Additionally, issue and workflow management facilitate human-led improvement initiatives. Ultimately, this comprehensive approach allows you to construct a more detailed and accurate representation of your data, employing techniques from entity resolution to complex deduplication and householding, thereby enriching your understanding even further.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
starts at $10000/user per year
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Data Ladder
Founded
2006
Country
United States
Website
dataladder.com
Vendor Details
Company Name
MIOsoft
Founded
1998
Country
United States
Website
www.miosoft.com/products/miovantage/index.html
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge