Configuration Engine



  • Connects to various data stores including Amazon Redshift® and Google BigQuery®
  • Discovers data content, classifies and generates trainable meta data structure
  • Allows users to impart additional knowledge
  • Validates meta data integrity with source data
  • Integrated security object model that offers unparallel control over the access
  • Offers audits in log form for analysis of data risks and integrity issues

Key Features


  • Content Recognition
  • Dynamic Transformations
  • Commonalities
  • Analytical Structures
  • Formulae with X-source data
  • Semantic Recognition
  • Semantic Context
  • Visualization Rules
  • Default aggregations
  • Content level security


X-Data Discovery And Validations

  • Works with structured and unstructured data sources
  • Content based discovery
  • Recognizes structure and content relationships
  • Ambiguity resolution in content
  • Collaborative
  • Distributive knowledge modeling

Machine learning and AI enabled

  • Context Modeling
  • Classifiers to recognize various entities
  • AI enabled X-source querying based on Adaptive intelligence
  • Entity similarity modeling
  • Computer vision technique to generate Knowledge from design documents

Enterprise Knowledge Governance

  • Knowledge distribution management
  • De-centralized administrative controls on Knowledge repository
  • Inherited security from sources
  • Dynamic integrity and security management

Adaptive to industry/Customers

  • Adaptive Knowledge management
  • All the discovered knowledge can be customized (semantic, visualization, transformation, formula, analytic structures etc.)

Data Governance

Configuration Engine Processes
Meta data and Virtualization Data Orchestration and Aggregation Data Presentation and Audits
Data availability and accessibility Data Completeness Access rights and data completeness validations during in-memory data integration Data verification capability, Data aggregation and drill down accessibility controls
Data ownership
Data Integrity and consistency Data relationships, statistics and standardization Configuration and transparency allows the users to verify Accuracy and Consistency Feedback, Adaptive and collaborative correction of meta data
Centralization of definitions and collaboration
Data Security and Auditability Security policies and Rules Application of security policies on data in orchestration services and record activities on unauthorized access Generate data audit and access logs audit to mitigate risks
Risk management


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