Autonomous Mastering Data Mesh Management with

VulcanLabs Enterprise

Autonomous Data Mesh based Master Data Management Platform to discover relationships and link data to a common point of reference, called a Best Version of Truth

Autonomous Data Mesh

Unlike many of our competitors, Vulcan.ai is built on the concept of an Autonomous Data Mesh. This modern approach leverages distributed data and processing capabilities, allowing us to provide a highly scalable and adaptable solution for managing master data and integrating diverse data sources. Our platform automates many data management tasks, reducing the need for manual intervention

Generative AI-Based Access Patterns

Vulcan.ai introduces Generative AI-based consumption access patterns. This feature enables users to interact with our Data Products in a more intuitive and efficient manner, enhancing the usability and accessibility of integrated data.

Semantic Layer

We create a semantic layer of an organization's data, presenting it as Domain-centric Data Products. This goes beyond what traditional MDM and integration solutions offer, providing a more contextual and user-friendly way to access and utilize data.

AI/ML Integration

Vulcan.ai fully embraces AI and machine learning, not just for data management but also for automating various tasks related to entity recognition, clustering, consolidation, data quality, and profiling. This level of automation significantly reduces the time and effort required to maintain and manage data.

Data Mesh Principles

We adhere to Data Mesh Architecture principles, ensuring that the best version of truth is exposed as a Data Product. This aligns with modern data management practices and enables organizations to make more informed decisions based on high-quality data.

Capabilities

Minimal or Zero Configuration
  • Auto detect input file type
  • Entity Recognition and Auto Language detection
  • Inference Clustering Rule from input data
  • Inference Consolidation Rule from input data
  • Inference Data Quality and Profiling Rule
Mastering Data Lake - Single Version of Truth
  • Single Version of Truth
  • Single well-defined version of all the data entities in a Data Lake
  • Offering best version of truth record to Data Scientist
No schemas to maintain/change

Quicker to adapt to ever-changing business needs

Highly Scalable Clustering and Consolidation Framework
Data linking and integration for internal and external data sources

Bring all the data together for better decisions, analytics, and answers

Mastering Data Lake
  • Single Version of Truth
  • Single well-defined version of all the data entities in a Data Lake
  • Offering best version of truth record to Data Scientist
  • Best version of Truth exposed as Data Product adhering to Data Mesh Architecture
Autonomous system leverages AI/ML technologies to automate data management related task rule generation process:
  • Entity Recognition and Language detection
  • Clustering and deduplication task
  • Consolidation task
  • Data Quality and Profiling Task
  • Data Catalog and other data governance rules
No schemas to maintain/change
  • Quicker to adapt to ever-changing business needs
  • Designed to handle a large volume of data efficiently (Clustering and Consolidation)
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