Data Integration & Virtualization
A unified data layer, without bottlenecks and without replicating everything
When data lives in different systems, keeping it aligned through copies and fragile integrations becomes an ongoing cost — and a source of errors. We organize your data without bottlenecks using ETL/ELT, real-time streaming, and Change Data Capture (CDC). With data virtualization, we expose a unified layer without physically replicating the data.
The service in brief
- Service
- Data integration and virtualization: ETL/ELT, streaming, CDC, and data virtualization.
- When you need it
- Data is spread across heterogeneous sources, and keeping it aligned through copies and fragile integrations costs too much.
- R.O.C.E. phase
- Evolve: the fourth phase of the Miriade R.O.C.E. methodology (Recover · Optimize · Control · Evolve).
- Scope
- Heterogeneous data sources, ETL/ELT pipelines, real-time flows, Change Data Capture, and virtual layers.
- Approach
- Integrate without bottlenecks and unify without physically replicating data.
- Distinct from
- The assessment/rationalization (the diagnosis) and platform modernization (Data Platform Modernization).
When data sources don't talk to each other
The service fits when data is spread across different systems and you need a reliable way — often in real time — to integrate it and make it accessible from a single point.
The integration toolkit
ETL/ELT
Design and optimization of extract, transform, and load flows to integrate data reliably and without bottlenecks.
Real-time streaming
Real-time data flows that feed analytics and processes that cannot wait for the nightly batch.
Change Data Capture (CDC)
We propagate only the changes made at the source, reducing load and latency and keeping systems aligned.
Data Virtualization
We expose a unified data layer over heterogeneous sources without physically replicating them: data is accessed where it lives.
Unify without replicating
With data virtualization, you expose a unified layer without physically copying the data.
Fewer copies mean less storage, fewer inconsistencies, and fewer integrations to maintain. Data stays where it is but becomes accessible from a single point, consistent and governed — the ideal foundation for BI, analytics, and AI.
Success stories
Documented Miriade work on data integration and virtualization.
Data governance with data virtualization
Bridging the gap between heterogeneous data sources by exposing a unified layer, without physically replicating the data.
Learn more Monthly tech challengeA DAG generator for Airflow
Standardizing the creation of Airflow DAGs (directed acyclic graphs) to reduce technical debt and speed up data integration.
Learn moreThe technologies we use
Some of the technologies and platforms we work with on this service.
From fragmentation to a governed ecosystem
Integration and virtualization are one of the ways the data ecosystem, once rationalized, becomes an asset again.
Data Ecosystem Assessment & Rationalization
Analysis and rationalization of the data environment: fewer tools, more coherence.
Data Integration & Virtualization
Integration and virtualization: a unified data layer without replication.
You are hereData Platform Modernization
Modern architectures (Data Fabric, Data Mesh) to break down silos.
EvolveAI-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
What is the difference between integration and virtualization?
Integration moves and transforms data (ETL/ELT, streaming, CDC). Virtualization exposes a unified layer without copying it. The two are often combined.
Do I need to replicate data in a single place?
Not with data virtualization: data is accessed where it lives, reducing storage, costs, and inconsistencies. Where needed, ETL/ELT and streaming remain available.
Does it work in real time or only in batch?
Both: streaming and CDC for real time, ETL/ELT for batch flows. We choose based on the use case.
How is it different from Data & Pipeline Acceleration?
That service accelerates an existing pipeline to reduce its run time. This one designs the integration and the unified layer over heterogeneous sources.
Can it make legacy systems and new technologies coexist?
Yes. It is one of the typical scenarios, with governed, reliable flows between old and new.
Do I need an assessment first?
It helps. The Data Ecosystem Assessment rationalizes the ecosystem, so integration and virtualization start from an orderly foundation.
Want a single point of access to your data?
Tell us which sources you need to integrate and on what timelines. With ETL/ELT, streaming, CDC, and data virtualization, we build a unified, consistent layer ready for BI, analytics, and AI.
A single point of access to your data
Tell us which sources you need to integrate and on what timelines (real time or batch). We design the integration and, where it makes sense, a unified virtual layer.
We use the data you submit only to contact you about this request.
