Data Platform Modernization
From the traditional data warehouse to lakehouse, Data Fabric, and Data Mesh: breaking down silos
Monolithic architectures and legacy data warehouses now show serious limits: rigid scalability, high latency, rising maintenance costs — and silos the business cannot use. We do more than move data to the cloud. We design modern, distributed architectures — Data Fabric and Data Mesh — that break down silos, democratize data access, and ensure interoperability across heterogeneous systems.
The service in brief
- Service
- Design and modernization of the data platform toward modern distributed architectures.
- When you need it
- The legacy data warehouse can no longer keep up: it scales poorly, costs too much, and keeps data locked in silos.
- R.O.C.E. phase
- Evolve: the fourth phase of the Miriade R.O.C.E. methodology (Recover · Optimize · Control · Evolve).
- Scope
- Data warehouses, data platforms, data management platforms (DMPs), distributed architectures (Data Fabric, Data Mesh), and lakehouses.
- Approach
- Not just moving data to the cloud, but designing architectures that democratize data access.
- Distinct from
- The assessment (the diagnosis), integration (Data Integration & Virtualization), and cloud migration.
When the data platform can no longer keep up
The service fits when the existing data architecture holds the business back: it scales poorly, costs too much, or keeps data locked in silos that no one can use.
The architectures we build
From Data Warehouse to Lakehouse
An evolution from the traditional data warehouse to lakehouse architectures that are more scalable and elastic, without disruptive overhauls.
Data Fabric
An integrated data fabric that connects heterogeneous sources and simplifies governed data access across the organization.
Data Mesh
A distributed model that treats data as a product and gives ownership to domains, removing central bottlenecks.
DMP Modernization
Upgrading existing data management platforms to make them leaner, more responsive, and more interoperable.
Don't just move data: democratize it
We do more than move data to the cloud: we design architectures that democratize data access.
Breaking down silos does not mean centralizing everything in one place. It means making data accessible, interoperable, and governed across heterogeneous systems — the foundation the business, and then AI, need to actually use it.
Success stories
Documented Miriade engagements in data platform modernization, with customer context and measurable results.
Data products for luxury fashion
A huge volume of behavioral data was technically out of reach for granular analysis.
Learn more Case study · Cybersecurity companyNear real-time data on Kubernetes
Handling highly variable data flows with real-time updates and customizable, scalable reporting.
Learn more Case study · HVAC leaderScalable time series database
Ingesting hundreds of thousands of rows per second from IoT devices with minimal compute resources.
Learn moreThe technologies we use
Some of the technologies and platforms we work with on this service.
From fragmentation to a governed ecosystem
Platform modernization is the step where the data ecosystem, once rationalized and integrated, becomes a solid, scalable foundation.
Data Ecosystem Assessment & Rationalization
Analysis and rationalization of the data environment: fewer tools, more coherence.
EvolveData Integration & Virtualization
Integration and virtualization: a unified data layer without replication.
Data Platform Modernization
Modern architectures (Data Fabric, Data Mesh) to break down silos.
You are hereAI-Ready Data & RAG Enablement
Data, documents, and knowledge bases ready for LLMs, RAG, and AI agents.
EvolveCloud Migration & Optimization
Migration and optimization of data, applications, and workloads in the cloud.
Frequently asked questions
How is it different from the Data Ecosystem Assessment?
The assessment rationalizes what exists and defines the target architecture. Modernization builds it. The first prepares the second.
Data Fabric or Data Mesh: which is better?
It depends on the context: organization, domains, maturity, and goals. We evaluate both with you. There is no one-size-fits-all answer.
Do I have to throw away my data warehouse?
No. It evolves progressively toward lakehouse and distributed architectures, preserving what works.
How is it different from Cloud Migration & Optimization?
Migration moves data and workloads to the cloud. This service redesigns the data architecture. The two are often combined.
Does it really democratize data access?
Yes, that is the goal: break down silos and make data accessible, interoperable, and governed across the organization.
Is it designed for AI too?
Yes. A modern data platform is the foundation that lets analytics and AI work on reliable data at scale.
Want a data platform ready for the future?
Tell us what your data architecture looks like today and where it holds you back. Together, we design a progressive, sustainable evolution toward lakehouse, Data Fabric, or Data Mesh.
A data platform ready for the future
Tell us what your data architecture looks like today and where it holds you back. Together, we assess a progressive evolution toward lakehouse, Data Fabric, or Data Mesh.
We use the data you submit only to contact you about this request.
