HOPEX Information Architecture: Manage data as enterprise asset with data modeling tool

HOPEX Information Architecture encompasses all data layers from physical and logical data modeling to conceptual data modeling. It enables information managers and data architects to create and manage business glossaries, as well as data dictionaries. It automates business data lineage between business data and technical data to analyze the impacts of change. It also allows to seamlessly transform physical data models into logical models and reciprocally.

HOPEX Information Architecture is integrated into a single platform with other practices such as business process analysis, application portfolio management and risk management, providing a comprehensive view into enterprise assets coupling data, applications and business perspectives. Also, by working in a single platform, various stakeholders share the same level of information to make collaborative, well-informed decisions about the governance of their data.*

With HOPEX Information Architecture, Information Managers and Data Architects can:

  • Quickly adjust to continuous market changes and perform impact analysis through business data lineage
  • Get a deep understanding of all the business concepts using a common business glossary
  • Ensure continuity between business information and data using a single platform
  • Design data models independently of their physical implementation
  • Determine opportunities for improvement in monetization, analysis, privacy, compliance, and security. 

HOPEX Information Architecture Key Features

Conceptual Data Modeling

Model and update information architecture 

  • Use semantic models to build consistent representations of the organization including business concepts, their relationships and lifecycles 
  • Create business dictionaries that collect and structure a set of business concepts
  • Create business information maps at the business layer
  • Develop business models to capture information exchanges, and manage key information assets 
  • Define business information views and business data areas
  • Create computation rules that describe how data is processed
  • Link conceptual data to logical and physical data. View all realized objects (conceptual data and its components) and realizer objects (logical and physical data)

Assess information consistency 

  • Evaluate deviation at an execution level 
  • Enhance merging and consistency with recommended corrective actions (action plans) 

Generate relevant reports 

  • Create various reports based on business dictionaries, term definition lists, synonyms, and components —all with on-demand translation capabilities 
  • Produce reports to view the implementation of dictionary elements in other parts of the architecture, depending on the desired perspective: business, logical and physical.

Logical Data Modeling

Logical Data design

  • Design data independently of their physical data implementation
  • Design data, relationships, and attributes using data entity diagrams (based on UML)
  • Define the logical data model structure through the use of class and class view components
  • Create data dictionaries corresponding to a set of logical data
  • Assign user roles on logical data components, such as classes and data dictionaries
  • Allow the edition of a subset of a class property
  • Use database trees to define the list of data dictionaries used in a database
  • Define data area for data stores used by applications
  • Create computation rules that describe how data is processed


  • Automatically create and link the corresponding business concepts when designing logical/physical data
  • Automatically connect logical/physical data items to conceptual data items (classes/entities, attributes)
  • Initialize business dictionary directly from the logical/physical layer
  • Associate logical/physical data to business data (concepts, components) through realization matrices
  • Link applications to data of a data dictionary and define data usage (CRUD Create, Read, Update, Delete)
  • View data domains, classes and tables, as well as applications and data stores tied to a data dictionary

Physical Data Modeling 

Database Modeling 

  • Represent physical data models using relational diagrams 
  • Automate the transformation of logical data models into physical data models 
  • Map between logical data model objects and relational objects 
  • Use intuitive denormalization wizards for logical data and physical data
  • Automatically create and link the corresponding business concept when designing physical data
  • Initialize business dictionary directly from the physical layer
  • Associate physical data to business data through realization matrices

Database Design 

  • Use specialized editors for Views, Triggers, and Stored Procedures 
  • Design DBMS-specific physical modeling with: 
    • Full support of SQL grammar for Oracle, DB2, SQL Server, and MySQL 
    • Intelligent editor for implementation and optimization of SQL 
  • Use database reverse-engineering tool to create the corresponding tables and columns in the HOPEX repository 

Extensive Database Support and Rules Database Alignment 

  • Reverse-engineer database schemas for relational DBMSs
  • Use neutral and DBMS-specific data types
  • Generate SQL code for the majority of relational DBMSs, such as Oracle, DB2, Teradata, PostgreSQL, SQL Server and MySQL
  • Generate code incrementally to implement updates to physical models

HOPEX is our comprehensive lineup of integrated software bringing together industry-leading practices in enterprise architecture (EA), IT portfolio management (ITPM), business process analysis (BPA), and governance, risk, and compliance (GRC) into a single platform. Integrated into a single enterprise repository, our HOPEX solutions give you an interactive view of all your business and IT components – including their dependencies – and help you drive business and IT transformation.