Create and Manage Enterprise Data Models | Info-Tech Research Group

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

1. Setting the stage

Prepare your environment for data architecture.

2. Revisit your SDLC

Revisit your SDLC to embed data architecture.

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.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

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.

Table of Contents

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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

Search Code: 96013
Last Revised: January 27, 2021

TAGS:

Conceptual model data modeling Data Architecture SDLC Business Architecture Enterprise Architecture Logical modelling Data Lineage Data Traceability

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