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Modernize Data Architecture for Measurable Business Results

Enable the business to achieve operational excellence, client intimacy, and product leadership with an innovative, agile, and fit-for-purpose data architecture practice.

  • Data architecture projects have often failed in the past, causing businesses today to view the launch of a new project as a costly initiative with unclear business value.
  • New technologies in big data and analytics are requiring organizations to modernize their data architecture, but most organizations have failed to spend the time and effort refining the appropriate data models and blueprints that enable them to do so.
  • As the benefits for data architecture are often diffused across an organization’s information management practice, it can be difficult for the business to understand the value and necessity of data architecture.

Our Advice

Critical Insight

  • At the heart of tomorrow’s insights-driven enterprises is a modern data environment anchored in fit-for-purpose data architectures.
  • The role of traditional data architecture is transcending beyond organizational boundaries and its focus is shifting from “keeping the lights on” (i.e. operational data and BI) to providing game-changing insights gleaned from untapped big data.

Impact and Result

  • Perform a diagnostic assessment of your present day architecture and identify the capabilities of your future “to be” environment to position your organization to capitalize on new opportunities in the data space.
  • Use Info-Tech’s program diagnostic assessment and guidance for developing a strategic roadmap to support your team in building a fit-for purpose data architecture practice.
  • Create a data delivery architecture that harmonizes traditional and modern architectural opportunities.

Modernize Data Architecture for Measurable Business Results Research & Tools

Start here – read the Executive Brief

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

1. Develop a data architecture vision

Plan your data architecture project and align it with the business and its strategic vision.

2. Assess data architecture capabilities

Evaluate the current and target capabilities of your data architecture, using the accompanying diagnostic assessment to identify performance gaps and build a fit-for-purpose practice.

3. Develop a data architecture roadmap

Translate your planned initiatives into a sequenced roadmap.

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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.

Need Extra Help?
Speak With An Analyst

Get the help you need in this 3-phase advisory process. You'll receive 8 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Develop a data architecture vision
  • Call 1: Plan your data architecture modernization project
  • Call 2: Create your data architecture vision

Guided Implementation 2: Assess data architecture capabilities
  • Call 1: Assess the capabilities of the organization’s data architecture practice
  • Call 2: Assess your enterprise data model
  • Call 3: Assess and plan the capabilities of each related architecture
  • Call 4: Assess your organization’s dynamic data architecture models

Guided Implementation 3: Develop a data architecture roadmap
  • Call 1: Review planned initiatives
  • Call 2: Discuss roadmap findings and next steps


Nurith Rochon

Rachel D'Hollander

Liam Grue


  • Michael Blaha, Author, Patterns of Data Modeling
  • Martin Sykora, Director, NexJ Analytics
  • David Birmingham, Senior Solutions Architect, Brightlight Consulting
  • Anne Marie Smith, Ph.D, Board of Directors, DAMA International
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