Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
A cloud-based data science platform provides meticulously curated and refined data, primed for immediate use. Companies encounter considerable hurdles, limited resources, and elevated expenses when handling their data before they can extract any meaningful insights. The data undergoes a process of ingestion, cleansing, storage, and access, culminating in analysis, which is where true value is derived. Our solution empowers clients to concentrate on their primary business functions instead of the costly, resource-intensive data lifecycle, as we manage those complexities for them. Additionally, our cloud-native platform supports real-time streaming analytics, capitalizing on the advantages of cloud architecture, allowing INQDATA to deliver swift and scalable access to both historical and real-time data while eliminating infrastructure complexities. This approach not only enhances efficiency but also ensures that businesses can adapt quickly to their evolving data needs.
API Access
Has API
Yes
API Access
Has API
No
Integrations
No details available.
Integrations
No details available.
Pricing Details
starts at $10000/user per year
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
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
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Data Ladder
Founded
2006
Country
United States
Website
dataladder.com
Vendor Details
Company Name
INQDATA
Founded
2023
Country
United Kingdom
Website
www.inqdata.ai/
Product Features
Data Cleansing
Address/ZIP Code Cleaning
Yes
Charting
No
Data Consolidation / ETL
No
Data Mapping
Yes
Multi Data Format Support
Yes
Phone/Email Validation
Yes
Raw Data Ingestion
No
Sample Testing
No
Validation / Matching / Reconciliation
Yes
Data Quality
Address Validation
Yes
Data Deduplication
Yes
Data Discovery
No
Data Profililng
Yes
Master Data Management
No
Match & Merge
Yes
Metadata Management
No
Product Features
Data Cleansing
Address/ZIP Code Cleaning
No
Charting
No
Data Consolidation / ETL
No
Data Mapping
No
Multi Data Format Support
No
Phone/Email Validation
No
Raw Data Ingestion
No
Sample Testing
No
Validation / Matching / Reconciliation
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
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No