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Create and Manage Enterprise Data Models

Keep track of your data with purpose-fit models.

  • Business executives don’t understand the value of Conceptual and Logical Data Models and how they define their data assets.
  • Data, like mercury, is difficult to manage and contain.
  • IT needs to justify the time and cost of developing and maintaining Data Models.
  • Data as an asset is only perceived from a physical point of view, and the metadata that provides context and definition is often ignored.

Our Advice

Critical Insight

  • Data Models tell the story of the organization and its data in pictures to be used by a business as a tool to evolve the business capabilities and processes.
  • Data Architecture and Data Modeling have different purposes and should be represented as two distinct processes within the software development lifecycle (SDLC).
  • The Conceptual Model provides a quick win for both business and IT because it can convey abstract business concepts and thereby compartmentalize the problem space.

Impact and Result

  • A Conceptual Model can be used to define the semantics and relationships for your analytical layer.
    • It provides a visual representation of your data in the semantics of business.
    • It acts as the anchor point for all data lineages.
    • It can be used by business users and IT for data warehouse and analytical planning.
    • It provides the taxonomies for data access profiles.
    • It acts as the basis for your Enterprise Logical and Message Models.

Create and Manage Enterprise Data Models Research & Tools

Start here – read the Executive Brief

Read our concise Executive Brief to find out why you should create enterprise data models, review Info-Tech’s methodology, and understand the four ways we can support you in completing this project.

Create and Manage Enterprise Data Models – Executive Brief
Create and Manage Enterprise Data Models – Phases 1-3

1. Setting the stage

Prepare your environment for data architecture.

Enterprise Data Models

2. Revisit your SDLC

Revisit your SDLC to embed data architecture.

Enterprise Architecture Tool Selection

3. Develop a Conceptual Model

Create and maintain your Conceptual Data Model via an iterative process.

4. Data Modeling Playbook

View the main deliverable with sample models.

Data Modeling Playbook
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What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Get the help you need in this 5-phase advisory process. You'll receive 9 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Establish the data architecture practice
  • Call 1: Scope requirements, objectives, and your specific challenges.

Guided Implementation 2: Business architecture and domain modeling
  • Call 1: Set the playing field.
  • Call 2: Identify business context and domain selection.

Guided Implementation 3: Harvesting Reference models
  • Call 1: Identify business entities within selected domain.
  • Call 2: Harvest Reference models.

Guided Implementation 4: Harvesting existing data artifacts
  • Call 1: Harvest application models.
  • Call 2: The use of the Data Glossary.

Guided Implementation 5: Build the Conceptual model
  • Call 1: Build the Conceptual model.
  • Call 2: Verify model with business for correctness.

Author

Dirk Coetsee

Contributors

  • Eric Carroll, Strategy, Architecture & Development Execution, Bank of Nova Scotia
  • Keith Enhagen, Manager Enterprise Architect, Bank of Montreal
  • Mike Lapenna, Senior Enterprise Architect Consultant
  • Mehrdad Novin, Senior Data Architect and Data Governance Consultant
  • Inna Pronina, Senior Data Architect Consultant
  • Raul Vomisescu, Senior Architect Consultant, Felmer Consulting

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