Semarchy Data Platform (SDP) Reviews & Ratings

Semarchy Data Platform (SDP)

4.7 out of 5 stars
Company Website for Semarchy Data Platform (SDP)

Ratings and Reviews 64 Ratings

Total 4.5 out of 5 stars
ease 4 out of 5 stars
features 4.5 out of 5 stars
design 4.5 out of 5 stars
support 4.5 out of 5 stars

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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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 Atlan?

Welcome to the modern data workspace, where discovering all your data assets, from tables to business intelligence reports, is made incredibly easy. Our sophisticated search technology, combined with an intuitive browsing interface, guarantees that finding the correct asset is straightforward. Atlan enhances the process of identifying low-quality data by automatically creating data quality profiles, which help users quickly recognize any existing issues. With capabilities such as automatic detection of variable types, analysis of frequency distributions, identification of missing values, and detection of outliers, Atlan addresses every facet of data quality management comprehensively. This platform streamlines the complexities associated with effectively governing and managing your data ecosystem. Furthermore, Atlan’s smart bots scrutinize SQL query histories to create data lineage maps and pinpoint personally identifiable information (PII), facilitating the development of dynamic access policies and ensuring robust governance. In addition, those who lack a technical background can easily conduct queries across multiple data lakes, warehouses, and databases thanks to our user-friendly, Excel-like query builder. Not only that, but seamless integrations with popular tools like Tableau and Jupyter also enhance collaboration around data, significantly changing the way teams collaborate and share insights. This comprehensive strategy not only empowers users but also cultivates a more data-driven culture across organizations, encouraging informed decision-making at every level. Ultimately, Atlan revolutionizes the way organizations interact with their data, paving the way for greater innovation and efficiency.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Azure Marketplace
CLEAN_Data
Experian Email Verification
Google Cloud Platform
Google Maps
Jitterbit
Microsoft Azure
Web APIs by Melissa

Integrations Supported

Anomalo
Apigene
Colrows
Google Data Studio
Grok Bot
MCPTotal
Mindfuel
STRM

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Semarchy

Date Founded

2011

Company Location

United States

Company Website

www.semarchy.com

Company Facts

Organization Name

Atlan

Date Founded

2018

Company Location

India

Company Website

atlan.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

Big Data

Collaboration
High Volume Processing

Data Collaboration

Not specified

Data Contract

Not specified

Data Discovery

Contextual Search
Data Classification
Data Matching
Self Service Data Preparation
Sensitive Data Identification

Data Fabric

Not specified

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Policy Management
Roles Management

Data Lineage

Not specified

Data Management

Data Quality Control
Information Governance
Master Data Management

Data Quality

Data Discovery
Data Profililng
Master Data Management
Metadata Management

ETL

Data Quality Control
Job Scheduling
Metadata Management
Version Control

Master Data Management

Data Governance
Data Masking
Data Source Integrations

Metadata Management

Not specified

PIM

Data Quality Control
Documentation Management
Version Control

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