Semarchy Data Platform (SDP)
4.7 out of 5 starsComposable DataOps Platform
5.0 out of 5 starsRatings and Reviews 64 Ratings
Ratings and Reviews 4 Ratings
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 Composable DataOps Platform?
Composable serves as a robust DataOps platform tailored for enterprises, empowering business users to develop data-centric products and formulate data intelligence solutions. This platform enables the creation of data-driven offerings that utilize a variety of data sources, including live streams and event data, irrespective of their format or structure. With its intuitive and user-friendly visual editor for dataflows, Composable also features built-in services to streamline data engineering tasks, in addition to a composable architecture that promotes both abstraction and integration of diverse analytical or software methodologies. As a result, it stands out as the premier integrated development environment for the exploration, management, transformation, and analysis of enterprise-level data. Moreover, its versatility ensures that teams can adapt quickly to changing data needs and leverage insights effectively.
Integrations Supported
Amazon Web Services (AWS)
Azure Marketplace
Microsoft Azure
CLEAN_Data
Experian Email Verification
Integrations Supported
Amazon Web Services (AWS)
Azure Marketplace
Microsoft Azure
Adobe Marketo Engage
Amazon Redshift
Anaplan
Azure Data Lake Storage
Domo
API Availability
API Availability
Has API
Pricing Information
Pricing not provided
Pricing Information
$8/hr - pay-as-you-go
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
SaaS
Windows
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based 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
Composable Analytics
Company Location
United States
Company Website
composable.ai
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
Artificial Intelligence
For Sales
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Catalog
Not specified
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 Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Engineering
Not specified
Data Intelligence
Not specified
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
DataOps
Not specified
ETL
Not specified
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Marketing Analytics
A/B Testing
Campaign Management
Channel Attribution
Customer Journey Mapping
Dashboard
Performance Metrics
Predictive Analytics
ROI Tracking
Social Media Metrics
Website Analytics
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization