System Integration & Data
We connect ERP, CRM and your other systems so each customer is one record and reports need no manual stitching.
Benefits you can expect
Data is entered once and appears in every system that needs it. Managers see up‑to‑date figures throughout the working day. Each system receives only the data it is allowed to see, and every request is logged. Integrations cost less to maintain, because one shared design replaces separate links between every pair of systems. We set up the exchange between your systems, keep one master list of customers and products, and monitor data quality.
What’s included
- Exchange via APIs and events
- Master data management (MDM)
- Connecting legacy systems
- Data quality control
Problems we solve
One customer has several records
Each customer has one master record, and every system refers to it.
Reports are stitched by hand
Data from different systems reaches reports on its own, with matching names and codes.
A new connection takes months
A new system plugs into the existing exchange, with no rework of the links already running.
Updating one system breaks the others
Each system updates at its own pace, while the rest keep getting data in the format they expect.
Nobody knows where a figure came from
For every figure in a report, you can see which system supplied the data and when.
Data sometimes goes missing between systems
A failed transfer is retried automatically, and whoever is responsible is alerted at once.
When you need it, and when you don’t
You need it
- several systems keep the same customer or product data
- you are rolling out a new ERP or CRM
- the company is merging systems after a merger or acquisition
- AI projects stall on duplicate data
You don’t
- two or three systems already share data through reliable APIs: keep that exchange running
- data needs a one‑off move to a new system: that is a migration project, not ongoing integration
Our approach
- 01
Data owner first, platform second
The technical work takes months, and agreeing who owns the data often takes longer. So we name an owner before choosing a platform.
- 02
The simplest design that works
For a few systems we don’t buy a large integration platform for the future. Every format is described, and changes are checked before release.
- 03
AI finds duplicates, people merge
AI proposes similar records and explains the match. People merge them, and without AI, duplicates are found by rules.
Project stages
- 3–4 weeks
Data audit
Which systems exchange what, where duplicates and conflicts sit.
- 4–6 weeks
Architecture
The exchange design, one master list and who owns the data.
- 2–3 months
Pilot
One type of data, usually customers, in two or three systems.
- 6–12 months
Rollout
The remaining systems and data, one connection at a time.
- ongoing
Data quality
Regular checks, without which the master list drifts apart within two years.
Platforms & standards
Informatica MDM · Reltio · Profisee · IBM InfoSphere MDM · UnityBase
Apache Kafka · RabbitMQ · MuleSoft · WSO2 · Kong · Debezium
Informatica Data Quality · Collibra · Atlan · Microsoft Purview
DAMA‑DMBOK · OpenAPI 3.1/3.2 · AsyncAPI 3.0 · ISO/IEC 27001 · GDPR · Data Act
Questions
How long does MDM take?
A pilot on one entity takes 2–3 months after audit and design; a full rollout in a large company takes 12–18 months.
What about legacy systems without APIs?
We read database changes via CDC, use RPA as a stopgap or put a service with an API in front of the system. The choice depends on risk and how soon the system is retired.
How is MDM different from a data warehouse?
A data warehouse serves analytics: it keeps history and only reads data. MDM keeps the master records and sends them back to working systems.
Further reading
Let’s talk about your systems
Thirty minutes with an architect to see how your systems share data and where to start.