MDP vector

Designing an Effective Modern Data Platform

We design modern data architectures that help you deliver decision-quality data to the right people at the right time—reducing the friction between data producers and data consumers.

The Challenge

When your legacy data architecture is straining to support data growth and complexity, and you can no longer meet the needs of your data consumers, it’s time to plan a Modern Data Platform.

A Modern Data Platform—an MDP—uses flexible architectural components, with teams drawing on repeatable design patterns and a tailored D&A operating model to fill gaps left by traditional D&A processes and speed time-to-insight.

But with so much at stake, transitioning to a modern platform is tough to get right. An effective MDP must address the entire business data lifecycle:

  • The pipes that carry data
  • The platforms that manage and store data
  • Database engines that prepare and analyze data
  • Dashboards and apps that consume data
  • Machine learning pipelines that uncover data insights, and
  • A governance layer that connects people to trusted data and makes data findable.

Unfortunately, an MDP is not a switch you flip or a thing you buy. Without careful planning, you may find yourself with a different flavor of the same “wild west” architecture, with failed pipelines, poor performance or runaway storage costs. And even the best program will fail if you don’t enable talent to new disciplines and adapt the program to the company’s culture.

With so many moving parts, it’s difficult for a D&A team to plan a successful shift to a Modern Data Platform—or even know where to start—and keep doing their jobs.

D&A leaders are asking:

Do I have the architecture, processes and skills we need to support a Modern Data Platform that delivers real value to the business?

How do I select from a crowded field of platforms? Should I pick best-of-breed components or commit to one cloud provider?

How do I build the processes and patterns that enable my team to deliver data products in a whole new way?

D&A leaders are asking Img

Why is it difficult?

It takes real-world experience to plan, implement, support and scale a Modern Data Platform.

There is tremendous pressure on data architecture teams to navigate a crowded field of platforms and rapidly evolving techniques to build data and analytics pipelines that can keep pace with the expectations of executives and business users, even as their data needs grow and grow more complex.

And selecting components is never enough—a successful MDP requires building a D&A strategy and operating model that aligns with the company’s strategy and meets the real needs of your data consumers.

My team spends more time tuning our platform than providing new insights and capabilities to our data consumers.

Since my platforms and data architecture are brittle, any small change is slow, complex, and high risk.

My team needs to enable our business consumers to help themselves with data, use it with confidence and support their curiosity.

Our Approach


Define an operating model strategy & success criteria. We help you define what value your MDP will provide, to whom and how you will run the platform.


Map stakeholder needs to platform capabilities. We conduct interviews and discovery across your organization to define what your stakeholders need, from data production to consumption, and we help you prioritize your most critical platform capabilities.


Create something tangible. We pilot an end-to-end, greenfield platform including a high impact business use case. Then we review, enable and plan a roadmap to scale it.

MDA ebook

Download our Guide to Modern Data Architecture, a comprehensive and opinionated report on designing a modern platform that reduces friction between data producers and data consumers.

Download A Guide to Modern Data Architecture

In The Guide to Modern Data Architecture from Axis Group you'll learn about the importance of:

  • Modern data capabilities, components and design patterns, such as orchestration, x-as-code, testing, metadata-driven development, composability and data drift
  • The shift to modern data principles and approaches, including how to focus on serving users, ways to maximize automation, and measure success
  • How DataOps helps, from picking the right operating model to using design thinking to enhance output to applying change management messages
MDA ebook

Successful Customers

Fahad Bijle, Director Enterprise Analytics and Data Strategy

Axis Group is my trusted D&A partner. Their methodologies and expert teams help me solve my most complex D&A challenges.

Fahad Bijle

Director Enterprise Analytics and Data Strategy @ Froedtert Health

Ramzi Braham, CIO ECI International

Thanks to the advice and recommendation we got from Axis Group, we were able to implement a modern platform in a record time.

Ramzi Braham

Chief Information Officer @ Electrical Components International

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Axis was instrumental in planning and realizing our data and analytics strategy. They helped to bring us out of the dark ages and held our hands as we took our first few steps. Thanks to their help, we’re flying now!

Ryan Young

Business Intelligence Manager @ GlacierBancorp

Marcel Meyer, Head of Data Governance and Management - Commercial Excellence at Siemens Healthineers

What I love about Axis is that they are laser-focused on solving the problem at hand.

Marcel Meyer

Head of Data Governance and Management - Commercial Excellence @ Siemens Healthineers

Case Studies

We have successfully delivered data & analytics solutions to customers in many industries, for various business functions. Not only did these solutions provide our customers with impactful insights, but they also generated excitement among business users, and created momentum for more data & analytics initiatives.

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Supplier Scorecard Puts Procurement Firmly in the Driver’s Seat


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Are you ready to take the next step
on your Data & Analytics journey?