Public-sector digital transformation

System Integration and Data Quality for Public Institutions

Many institutions run systems that do not exchange data, so staff enter the same information several times and the same question gets different answers. We connect existing systems, clean data and unify reference lists so that data becomes a reliable basis for work and reporting.

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What we offer

We start by mapping systems and data sources: which systems are in use, what data they hold, who owns it and where it is duplicated. We then identify priority integration points, such as passing applicant data between a portal and the workflow system, or synchronizing staff data between two systems.

We design integration interfaces and data exchange mechanisms and set data quality rules: mandatory fields, consistent formats, duplicate prevention and shared reference tables for regions, bodies and categories. Existing data is cleaned and matched, and everything is documented so the institution can maintain it.

Any exchange of data with other bodies takes place only on the institution's decision and within the legal framework and existing agreements between the bodies concerned.

Who it is for

Institutions with several systemsWhen systems do not talk to each other and data entry is duplicated.
Statistics and reporting unitsWhen figures differ depending on their source.
Ministries and their directoratesTo collect data from branches in a consistent format.
Ongoing digital transformation projectsTo make sure new systems connect to existing ones instead of creating new silos.

Problems we address

The same data entered manually into more than one system.
Conflicting figures in reports depending on the system or department.
Duplicate, incomplete or inconsistently formatted records.
Legacy systems with no documentation or integration interfaces.
No shared reference tables for names, codes and categories.

Tasks and deliverables

System and data map: An inventory of systems, data sources, data flows and the owner of each.
Integration design: Defining connection points, exchange method, formats, frequency and error handling.
Integration interfaces and tools: Developing APIs or scheduled exchange processes between systems.
Data quality rules: Mandatory fields, consistent formats, validation rules and duplicate prevention.
Data cleaning and matching: Resolving duplicate and incomplete records and unifying reference data with the institution's approval.
Technical documentation: Description of interfaces, data rules and maintenance procedures for the institution's team.

Who does what

What IAG does

Mapping systems and analysing data and data flows.
Designing the integration and data quality rules.
Developing and testing interfaces and exchange tools.
Carrying out cleaning and matching in coordination with data owners.
Documentation and knowledge transfer to the institution's technical team.

What specialists, partners and authorities do

The institution designates the owner of each dataset and who may view and change it.
The institution decides on any data exchange with other bodies under the legal framework and inter-agency agreements.
Data owners approve cleaning rules and matching results before they are applied.
The institution or the vendors of its current systems provide the necessary technical access and available documentation.

Practical example

Illustrative scenario

Connecting an application portal to the workflow system

Applications arrive via an online form and staff then re-enter them manually into an internal system.

Identifying fields shared by both systems and aligning their formats.
Developing an interface that passes the application automatically to the workflow system.
Sending the status back to the portal on every change.
Logging transfer errors and alerting the responsible person.
Periodic review of the quality of transferred data.

This is an illustrative scenario to explain the idea, not a client reference or an existing project.

How we work together

Inventory and analysis
Documenting systems, data, owners and duplications.
Prioritization
Choosing the integration points and data with the greatest effect on daily work.
Design
Agreeing the integration approach and quality rules with the institution.
Implementation and testing
Developing interfaces, cleaning data and testing results with users.
Operation and monitoring
Monitoring exchanges and data quality and handling errors.

Intended results

Less duplicate data entry.
More consistent figures across systems and reports.
Unified reference data that later systems can build on.
Documentation that enables the institution to maintain the integration.

What we need from you

A list of systems in use, with information on their vendors and documentation.
Named data owners in the departments involved.
Controlled technical access to test environments or data copies according to the institution's policy.
Decisions on which data may be exchanged and within what limits.
A technical contact at the institution to receive the knowledge transfer.

Basis for cost and timeline

Cost depends on the number and type of systems, whether interfaces or documentation exist, the volume and condition of data, and security and hosting requirements. We recommend starting with one integration point with a clear effect and a defined scope, then expanding in phases.

Frequently asked questions

Can you connect to a legacy system without interfaces?

Often yes, through alternatives such as scheduled file exchange or reading from the database; this is decided after a technical review.

Do you delete data during cleaning?

No merging or deletion happens except under rules approved by the data owners, and a backup is kept.

Can data be exchanged with another ministry?

Technically yes, but the decision and the legal framework rest with the two institutions concerned.

Who owns the integration interfaces afterwards?

Interfaces and their documentation are handed over to the institution as agreed in the contract.

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