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ease
features
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support

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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

The growing abundance of essential business information presents both opportunities for gaining insights and risks of potential mistakes. IBM® InfoSphere® Master Data Management offers robust matching functionalities to align and address discrepancies in data, ensuring that you maintain the most current and precise understanding of your information. With the ability to access a reliable, all-encompassing 360-degree perspective on your customers and operational processes, users can engage in collaboration and foster innovation. Users can now harness the enterprise capabilities of InfoSphere Master Data Management within the secure, governed, and integrated environment of IBM Cloud Pak® for Data. This solution allows for the consolidation of enterprise-wide business data into an exceptionally accurate representation. Additionally, it enables the visualization of master, transactional, and Hadoop data, facilitating analysis by business users and helping to create a virtual golden profile of master data suitable for registry-style applications. By enhancing visibility and accessibility, organizations can drive more informed decision-making.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

SpiceX No 
Vertica No 

Integrations

SpiceX Yes 
Vertica Yes 

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 Yes 
Live Rep (24/7) Yes 
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 Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Data Ladder

Founded

2006

Country

United States

Website

dataladder.com

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/ibm-infosphere-master-data-management

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

PIM

Content Syndication Yes 
Data Modeling No 
Data Quality Control No 
Digital Asset Management No 
Documentation Management No 
Master Record Management No 
Version Control No 

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