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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
Great Expectations serves as a collaborative and open standard aimed at enhancing data quality. This tool assists data teams in reducing pipeline challenges through effective data testing, comprehensive documentation, and insightful profiling. It is advisable to set it up within a virtual environment for optimal performance. For those unfamiliar with pip, virtual environments, notebooks, or git, exploring the Supporting resources could be beneficial. Numerous outstanding companies are currently leveraging Great Expectations in their operations. We encourage you to review some of our case studies that highlight how various organizations have integrated Great Expectations into their data infrastructure. Additionally, Great Expectations Cloud represents a fully managed Software as a Service (SaaS) solution, and we are currently welcoming new private alpha members for this innovative offering. These alpha members will have the exclusive opportunity to access new features ahead of others and provide valuable feedback that will shape the future development of the product. This engagement will ensure that the platform continues to evolve in alignment with user needs and expectations.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Acryl Data
No
Amazon Redshift
No
Amazon S3
No
Apache Airflow
No
Apache Spark
No
Astro by Astronomer
No
Dagster
No
DataHub
No
Databricks
No
Flyte
No
Integrations
Acryl Data
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Apache Airflow
Yes
Apache Spark
Yes
Astro by Astronomer
Yes
Dagster
Yes
DataHub
Yes
Databricks
Yes
Flyte
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
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
Great Expectations
Website
greatexpectations.io
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 Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No