Semarchy Data Platform (SDP)
4.7 out of 5 starsOpenDQ
5.0 out of 5 starsRatings and Reviews 64 Ratings
Ratings and Reviews 1 Rating
What is Semarchy Data Platform (SDP)?
Semarchy Data Platform (SDP) provides an enterprise data management environment that unifies data integration, master data management, data quality, and governance within a single platform. The solution is built around the concept of reusable Data Products that package business information, processing logic, and access interfaces into independently managed components. Each Data Product can contain data entities, validation rules, transformation pipelines, APIs, semantic models, and descriptive metadata that define how information is structured and consumed. Built-in ownership and lifecycle management capabilities help organizations maintain accountability and consistency as data assets evolve. SDP supports a DataOps-oriented development process in which engineers design solutions using Visual Studio Code, track changes through Git, and manage releases with continuous integration and deployment pipelines. Automated testing and rollback functionality enable teams to validate modifications and recover from unsuccessful deployments without disrupting established data workflows. AI-powered design assistance helps users create data models, configure business rules, and accelerate the development of governed data assets. Integrated governance functionality includes data lineage, access management, quality controls, and metadata management to support trusted information throughout its lifecycle. Organizations can deploy the platform as a managed SaaS solution, within self-hosted infrastructure, or natively in Snowflake, depending on their technical and operational requirements. By replacing fragmented data management tools with a unified, reusable architecture, Semarchy Data Platform helps enterprises reduce integration complexity, accelerate data delivery, and provide consistent information for analytics, applications, and business operations.
What is OpenDQ?
OpenDQ offers an enterprise solution for data quality, master data management, and governance at no cost. Its modular architecture allows it to adapt and expand according to the specific needs of your organization's data management strategies.
By leveraging a framework powered by machine learning and artificial intelligence, OpenDQ ensures the reliability of your data.
The platform encompasses a wide range of features, including:
- Thorough Data Quality Assurance
- Advanced Matching Capabilities
- In-depth Data Profiling
- Standardization for Data and Addresses
- Master Data Management Solutions
- A Comprehensive 360-Degree View of Customer Information
- Robust Data Governance
- An Extensive Business Glossary
- Effective Meta Data Management
This makes OpenDQ a versatile choice for enterprises striving to enhance their data handling processes.
Integrations Supported
Amazon Web Services (AWS)
Azure Marketplace
Integrations Supported
Amazon Kinesis
Amazon S3
Apache Cassandra
Apache HBase
Apache Kafka
Apache Solr
Atom
Azure API Management
API Availability
API Availability
Pricing Information
Pricing not provided
Pricing Information
$0
License Free Software
Free Version
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
SaaS
Windows
Mac
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Semarchy
Date Founded
2011
Company Location
United States
Company Website
www.semarchy.com
Company Facts
Organization Name
Infosolve Technologies, Inc
Date Founded
2003
Company Location
United States
Company Website
www.infosolvetech.com
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Product Data Management
Bill of Material Management
Document Management
Formula Management
Product Analytics
Product Lifecycle Management
Testing Management
Version Control
Categories and Features
Customer Data Platforms (CDP)
Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Process Management
Roles Management
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization